Frequently Asked Questions - Image-Pro Plus
Find popular troubleshooting
and how-to resources
When the Image Pro Plus 7 shortcut icon is clicked, nothing happens.
This is related to HP pre-installed security software.
Go into Programs and uninstall "HP Device Access Manager"
Right-Click on the Image Pro Plus 7 shortcut on Windows’ desktop and select “Run as Administrator”.
On the registration Dialog select “Do not remind” and click the red ‘X’ in the upper right corner of the dialog.
Restart Image Pro and the dialog should no longer appear.
Media Cybernetics partners with Velquest.
VelQuestis a leading supplier of Compliance Management Systems, which virtually eliminates tedious manual paperwork, while providing a common platform for data exchange. They offer extensive products and services, especially in the pharmaceutical industry, focusing on 21 CFR Part 11 compliance issues. Through strategic cooperation, Image-Pro Plus operates in conjunction with the VelQuestSmartShell Technical Remediation Solution.
Image-Pro has the ability to add a personal electronic signature to image and report files.
The Audit Trail is similar to the macro recorder, but trageted at keeping a log of everything that is done in Image Pro on a daliy basis. When enabled (Choose Edit|Preferences... and check Generate audit trail log.), the Audit trail feature creates a log of the equivalent macro call for every action you perform in Image Pro Plus. In addition, each line is prefeaced with the full time and date that the action was performed.
Below is a sample of the audit trail log:
2001/10/22 16:19:22.310 Image-Pro Plus logging started.
2001/10/22 16:19:23.570 ret = IpAcqShow(ACQ_SNAP, 0)
2001/10/22 16:19:30.710 ret = IpDocMove(0, 0)
2001/10/22 16:19:30.710 ret = IpAppSelectDoc(0)
2001/10/22 16:19:30.820 ret = IpDocSize(349, 288)
2001/10/22 16:19:30.820 ret = IpWsLoad("C:\IPWin45\Images\DemoGrn.TIF","tif")
2001/10/22 16:19:40.210 ret = IpDocMove(22, 22)
2001/10/22 16:19:40.210 ret = IpAppSelectDoc(1)
2001/10/22 16:19:40.210 ret = IpDocMove(6, 24)
2001/10/22 16:19:40.210 ret = IpDocSize(349, 288)
2001/10/22 16:19:40.210 ret = IpWsLoad("C:\IPWin45\Images\DemoBlue.TIF","tif")
2001/10/22 16:19:40.270 ret = IpDocMove(44, 44)
2001/10/22 16:19:40.270 ret = IpAppSelectDoc(2)
2001/10/22 16:19:40.270 ret = IpDocMove(12, 48)
2001/10/22 16:19:40.270 ret = IpDocSize(349, 288)
2001/10/22 16:19:40.270 ret = IpWsLoad("C:\IPWin45\Images\DemoRed.TIF","tif")
2001/10/22 16:19:56.970 ret = IpCmChannelMerge3(0, 2, 0, 1, CM_RGB, 1)
2001/10/22 16:19:57.020 ret = IpDocMove(66, 66)
2001/10/22 16:19:57.020 ret = IpAppSelectDoc(3)
2001/10/22 16:19:57.020 ret = IpDocMove(18, 72)
2001/10/22 16:19:57.020 ret = IpDocSize(349, 288)
2001/10/22 16:20:04.600 ret = IpCmpShow( COMP_SHOW )
2001/10/22 16:20:07.240 ret = IpCmpShow( COMP_HIDE )
2001/10/22 16:20:18.550 ret = IpCoLocShow(1)
2001/10/22 16:20:26.190 Image-Pro Plus logging ended.
This log file give you a per session record of what was done to an image, and can be used as a guide for reproducing your actions. You may also notice that by simply removing the date and time at the beginning of each line, and wrapping the resulting text with Sub Subname() and End Sub statements you can very quickly generate a macro to repeat exactly what you just did.
Media Cybernetics software supports opening, manipulating and saving images in 8, 12, and 16 bit gray scale, 24, 36, and 48 bit color, 8 bit palette, and 32 bit floating point formats.
The problems that you may experience as a result of this fact are:
The 12 and 16 bit gray scale, 36 and 48 bit color, and 32 bit floating point formats can only be saved in TIFF (*.tif), Image-Pro Workspace (*.ipw) and Sequence (*.seq) files. If you wish to save an image in one of these formats to a different file type, you will first have to convert the image to 8 bit grayscale, 24 bit color or palette. This conversion is non-destructive - it actually makes a new copy of the image, but it will reduce the amount of information in the image.
Opening in other software products:
If you are saving images as TIFF (*.tif) and finding that they cannot be opened in other software, you can find out what which format has been used to store the image by choosing Edit|Information and looking at the Class item on the General tab of the Image Information dialog. Some other programs (such as Adobe PhotoShop) can open 16 bit gray scale and 48 bit color images, but very fewother programs can open 12 bit gray scale, 36 bit color and 32 bit floating point images. If you have images in 12 and 16 bit gray scale, 36 and 48 bit color, or bit floating point formats and are finding that they cannot be opened in other.
Many people have had troubles importing files with the .raw extension to Image-Pro Plus, since version 4.5.1 was released. This is because .raw is not a standardized format. Every software product and manufacturer that creates .raw files uses a different definition of the .raw format. Ours is based on the National Institutes of Health (NIH) .raw format. If this is causing a problem for you, you can disable the built-in .raw format and continue using the Flat File Descriptor that you have been using up until now.
This is done by adding a section to the IPWIN32.INI file. Use Notepad (Start|Programs|Accessories|Notepad) to edit this file add a section similar to the following:
In the above example the offending NIH (RAW) format is removed - if you want to remove more formats, just add more lines in the ReservedExts section. What you want to use in each of these lines is the file extension for the format (e.g. PIC for BioRad).
Note: You MUST have Image-Pro Plus v220.127.116.11 or later for this feature to work.
Create your AOI on the first frame of your sequence.
Go to Process...Operations.
Your Sequence will be listed as the "First Operand".
Select "Add" as the operation.
The "Second Operand" should be "Number" and set "0" as the number.
For "Put result in", select "New Image".
When you hit "Apply" your new sequence will be generated.
One way to enhance an image is to change the way intensity values are interpreted. For example, if your image was very dark overall, you could boost all the values by a certain amount. You might boost all values by 20 points, or flatten a range of intensities to a single value (e.g., set all intensities from 75 through 150 to 127).
Image-Pro gives you many tools and controls to manipulate the intensities within your image. Although you will see the effect of an index modification immediately upon your image, pixel changes are not actually written to your image. They are written to an intermediate "table" called a "Lookup Table" (LUT).
This is done so that intensity changes can be executed quickly, and so that they can easily be undone. When you are satisfied with the intensity changes you have made, you must make the changes permanent by either storing your image or explicitly writing the changes to the image bitmap using the Contrast Enhancement command.
The following intensity manipulation tools are provided by Image-Pro:
Brightness is a term used to describe the overall amount of light in an image.
In Image-Pro, brightness is modified using the "Brightness" slider control on the BCG Controls. This control affects the overall image. In a color image, the "Brightness" slider control adjusts luminance, which is the combined intensity of the RGB channels.
Brightness for an individual color channel can be modified using the "Brightness" control in the Contrast Enhancement dialog box.
When brightness is increased, you increase the value of every pixel in the image, moving each pixel closer to 255, or white. When brightness is decreased, you reduce the value in each pixel, moving it closer to 0, or black.
Contrast is a term used to denote the degree of difference between the brightest and darkest components in an image.
An image has poor contrast if it contains only harsh black and white transitions, or contains pixel values within a narrow range (an image whose values ranged from 100 to 140 would have poor contrast). An image has good contrast if it is composed of a wide range of brightness values from black to white. The amount of the intensity scale used by an image is called its "dynamic range." An image with good contrast will have good dynamic range.
In Image-Pro, contrast is modified using the "Contrast"slider control on the BCG Controls. This control affects the overall image.
In a color image, the "Contrast" slider control operates upon the luminance channel, which is the combined intensity of the RGB channels. Contrast for an individual color channel can be modified using the "Contrast" control in the Contrast Enhancement dialog box.
During a contrast operation, each pixel value is scaled by a contrast value, which serves to redistribute the intensities over a wider or narrower range. Increasing the contrast spreads the pixel values across a wider range, while decreasing contrast squeezes the values into a narrower range.
Gamma correction is a specialized form of contrast enhancement that is designed to enhance contrast in the very dark or very light areas of an image. It does this by changing the midtone values, particularly those at the low end, without affecting the highlight (255) and shadow (0) points.
Gamma correction can be used to improve the appearance of an image, or to compensate for differences in the way different input and output devices respond to an image.
In Image-Pro, Gamma adjustments are made using the "Gamma" slider control on the BCG Controls. In a color image, the "Gamma" slider control operates upon the luminance channel, which is the combined intensity of the RGB channels. The Gamma value for an individual color channel can be modified using the "Gamma" control in the Contrast Enhancement dialog box.
The Gamma control modifies an image by applying standard, nonlinear gamma curves to the intensity scale. A gamma value of 1 is equivalent to the identity curve, which has no effect on the image. An increase in the gamma value (setting it to a value greater than 1) will generally lighten an image and increase the contrast in its darker areas. A decrease in the gamma value (setting it to a value less than 1) will generally darken the image and emphasize contrast in the lighter areas.
Thresholding allows you to reduce your image to just two colors: black and white. This is done by specifying a range of intensities to be emphasized (set to white), and converting all others to black (0).
Thresholding is often used to segment an image in order to extract its important features, or to reduce an image to two intensity levels in preparation for a watershed or thinning filtering operation.
Thresholding is performed using the Threshold command on the Process menu. When this command is selected, you will be asked to specify the range of values you want emphasized (set to white).
The Threshold command operates upon gray scale values, so if you are working with a True Color (RGB-24) or Palette image, it must be converted (see the Convert to to command) to Gray Scale before it can be thresholded.
Histograms measure and illustrate in graph form, the brightness and contrast characteristics of an image. Histogram data can be created and viewed for data gathering and analytical purposes (discussed in more detail in the Intensity Analysis section), or can be manipulated for image enhancement purposes.
A histogram is created using the Histogram command on the Measure/Analysis menu. As you can see in the example below, the X-axis in a histogram represents the intensity scale (0 to 255 in this example), and the Y-axis measures the number of pixels in the image possessing that value.
When you are working with Gray Scale 8 images, the X-axis represents gray values 0 through 255. For other Gray Scale image types, the x-axis will represent the intensity range ( 0 to 4095 for Gray Scale 12). When working with True Color images, you can choose to measure either the image's combined luminosity or its separate color channels (e.g., Red or Green or Blue, Hue or Saturation or Intensity...).
A histogram will show you what kind of brightness/contrast deficiencies exist in an image. Images with low contrast will have histograms that are clustered around a very narrow portion of the color range. The position of the cluster will indicate whether the image is too dark, too light, or simply too gray,
Brightness, contrast and gamma (BCG Controls) adjustments modify the shape of a histogram. Contrast operations affect the width of a histogram; compressing it when it is decreased, and stretching it when it is increased.
A decrease in gamma brings out features in the lighter area of the image, by stretching the histogram in the upper region. An increase in gamma stretches the lower values, providing increased contrast in the darker areas.
A cumulative, or accumulated, histogram can also be used to assess the brightness and contrast characteristics of an image. An accumulated histogram measures the number of pixels that have a given pixel value or a lesser value. The result is an integral of the regular histogram distribution function.
The accumulated histogram indicates the evenness of the intensity distribution. An even distribution will produce a histogram that resembles a linear progression.
Accumulated histograms are created using the Accumulated command on the Report menu in the Histogram command window.
Image-Pro provides several ways to automatically reshape a histogram. Using the Contrast Enhancement command on the Enhance menu, you can optimize the brightness and contrast characteristics by directing Image-Pro to stretch the histogram to achieve the best possible contrast distribution for the given image. You can also use one of the specialized distribution functions provided by the Equalize command on the Enhance menu. These histogram redistribution functions enhance contrast and dynamic range in a nonlinear manner.
When you use the Equalize command, Image-Pro analyzes your image's accumulated histogram and redistributes it to fit the shape you specify:
¨ Linear: Distributes the histogram equally across the intensity scale. This function produces a high contrast image with the highest possible dynamic range.
¨ Bell: Distributes the histogram evenly around the center of the intensity scale. This function produces a high contrast image with less dynamic range than the "Linear" distribution.
¨ Logarithmic: Concentrates the histogram at the low end of the scale. This function produces a high contrast image with little dynamic range. It will tend to darken the image overall. Useful for stretching the contrast in a very light image.
¨ Exponential: Concentrates the histogram at the high end of the scale. This function produces a high contrast image with little dynamic range. It will tend to lighten the image overall. Useful for stretching the contrast in a very dark image.
Intensity analysis operations let you collect data from your image based upon the intensity values it contains. Image-Pro provides the following intensity analysis tools:
- Histogram Analysis
- Line Profile Analysis
- Bitmap Analysis.
Histogram analysis lets you create a histogram of an image or AOI. Line Profile analysis lets you plot the intensity values along a given line. Bitmap analysis allows you to display the values of individual pixels in a bitmapped image. Using the Save commands on the Histogram, Line Profile, and Bitmap Analysis file menus, you can store the results of your analysis to a file for use with other applications.
Although the analysis tools actually measure the intensity levels within your image, you can calibrate Image-Pro to express these values in units relevant to your application. For example, by setting Image-Pro's Std. Optical Density option on the Intensity Calibration dialog box, the intensity scale can be calibrated to standard optical density values used by most transmitted light experiments. You could also calibrate the intensity scale to indicate temperature, or protein content, for example.
Intensity calibration is performed using the Calibration command on the Measure menu.
See Reference Guide for more information about:
Filtering operations reduce or increase the rate of change that occurs in the intensity transitions within an image. Areas in which there are sudden or rapid changes in intensity appear as hard edges in an image. Areas where there are gradual changes produce soft edges.
Filtering acts to detect and modify the rate of change at these edges. It can increase the intensity differences in a soft edge to make it appear sharper, or reduce the intensity differences in a hard edge to smooth and soften it.
Filtering operations produce their effect by modifying a pixel's value based upon the values of the pixels that surround it. For example, blurring is accomplished by averaging all of the pixel values in a specified region, and replacing the center pixel with the averaged value. This produces reduced variation among neighboring pixels, which visually softens the image. A sharp black/white edge would be softened with intervening levels of gray.
Filtering techniques are divided into two categories: convolution filters (linear filters) and nonconvolution (nonlinear) filters. Both techniques accomplish their results by examining and processing an image in small regions, called pixel "neighborhoods." A neighborhood is a square region of image pixels, typically 3x3, 5x5 or 7x7 in size.
In Image-Pro spatial filtering is performed using the Filters command on the Process menu.
Enhancement or convolution filters process image neighborhoods by multiplying the values within a neighborhood by a matrix of filtering coefficients (integer values). This matrix is called a "kernel." It is the same size as the neighborhood that it is being applied to. The results of this multiplication are summed and divided by the sum of the filter kernel (see the Kernel tab dialog under the Filters command). The result replaces the center pixel in the image neighborhood.
THE CONVOLUTION FILTERING PROCESS
1. Each pixel in the image neighborhood is multiplied by the contents of the corresponding element in the filtering kernel.
2. The results from the multiplication are summed and divided by the sum of the kernel.
3. The result is scaled and boosted, and used to replace the center pixel in the image neighborhood.
Note - The convolution process always uses a neighborhood's original (unfiltered) pixel values as input. When, in the example above, the kernel's focus is moved to pixel 6, the filtering process will use pixel 5's original value, not the one it was just assigned by the convolution.
The following Enhancement filters are provided by Image-Pro:
- Lo-Pass: This filter blurs an image by modifying a pixel value to be more like its neighbors. This eliminates harsh edges by reducing the intensity differences between adjacent pixels. The Lo-Pass filter can be used to blur an image for aesthetic reasons, to eliminate detail in preparation for object segmentation, or to eliminate random image noise (see also Median Filter in the Nonconvolution/Morphological Filters section).
- Hi-Pass: This filter accentuates intensity changes in an image by modifying a pixel's value to exaggerate its intensity difference from its neighbors. This filter produces an image with harsh intensity transitions, and generally results in an image with only edges of high contrast visible. Fine detail with low contrast is usually lost to the background. This filter can be used when you need to pull out just the elements having high contrast to the image background.
- Gauss: Use this filter to soften an image by eliminating high-frequency information using a Gauss function. This has the effect of blurring sharp edges. The operation of the Gauss filter is similar to the LoPass filter, but it degrades the image less than the LoPass filter.
- Higauss: Use this filter when you want to enhance fine details. Its operation is similar to the unsharp masking technique (see the Sharpen filter below), but it introduces less noise in the process. It uses a Gaussian curve type of kernel. Available in 7x7 and 9x9 kernel sizes.
- Local equalization: This filter enhances the pixel contrast based on the histogram of the local neighborhood.
¨ Sharpen: This filter accentuates all edges within an image by significantly enhancing all intensity transitions in the image. This is accomplished using a technique called "unsharp masking," which essentially sharpens an image by subtracting its low-pass results from the original image (although this is the result, it is accomplished using the convolution process, not by actually subtracting a blurred image from the original). Sharpening is used to bring out fine detail in an image, or to re-focus an image that has been blurred.
- Flatten: Use the Flatten filter to even out background variations. This is often done to prepare an image for Count/Size operation if its objects are difficult to isolate because the background contains pixels of the same intensity as the objects of interest. Flatten reduces the intensity variations in the background pixels.
- Median: This filter smoothes an image by modifying pixels that vary significantly from their surroundings. This is accomplished by replacing the center pixel in a neighborhood with the median value of the neighborhood. Although median filtering will soften an image, it generally preserves its edges. This filter is particularly effective at removing random, high-impulse noise from an image (e.g., spots or points that vary significantly from the background).
- Rank: Select this filter if you want to remove impulse noise from an image. The Rank filter replaces the center pixel with a ranked pixel value from the kernel when the gray value difference is larger than the threshold value.
Note - If your image appears black after applying any of the above filters, use your Brightness, Contrast and Gamma controls to lighten the image and bring out the edge detail.
Convolution filters can be applied in kernels of 3 x 3, 5 x 5, or 7 x 7. Generally, the smaller the kernel, the more subtle the result. Appendix B, File Format Specifications of the Image-Pro Reference Guide, identifies the coefficients contained in each of the kernels used by the convolution filters described above.
- Sobel: This filter extracts and enhances edges and contours in an image by expressing intensity differences (gradients) between neighboring pixels as an intensity value. This is done by combining the difference between the top and bottom rows in a neighborhood, with the difference between the left and right columns, using the following formula:
(X2 + Y2)½
where: X = (C + 2F + I) - (A + 2D +G)
Y = (A + 2B + C) - (G + 2H +I)
In neighborhoods where there is no difference among values in the neighborhood the pixel's intensity is set to 0 (black); where there is the greatest possible difference, the pixel is set to 255 (white). The results are similar to the Roberts filter: highlighted edges against a dark background, but the Sobel filter is less sensitive to image noise. This generally results in an image with smoother, more pronounced outlines of only the principal edges.
- Roberts: This filter extracts and enhances fine edges in an image by expressing the differences between neighboring pixels (cross pairs) as an intensity value. In neighborhoods where there is no difference among values in the neighborhood the pixel's intensity is set to 0 (black); where there is the greatest possible difference, the pixel is set to 255 (white). Intermediate levels of gray reflect varying amounts of difference. The result is an image in which edges and contours are highlighted against a dark background.
Unlike most other filters, which use an odd-sized square neighborhood, the Roberts filter operates upon a 2 x 2 neighborhood. Since this neighborhood has no center, the pixel in the upper left-corner is the one replaced with a new value. Its filtered value is calculated using the following formula:
[(A - D)2 + (C - B)2]½
The Roberts filter enhances all edges within an image, even those introduced by noise.
Note - If your image appears black following a Roberts filter, use your brightness, contrast and gamma controls to lighten the image and bring out the edge detail.
- Laplacian: The Laplacian filter is an edge filter that accentuates intensity changes in an image by modifying a pixel's value to exaggerate its intensity difference from its neighbors. Its results are very similar to those of Hi-Pass. It produces an image with harsh intensity transitions, and results in an image with only edges of high contrast visible.
- Variance: Select this filter if you want to detect and emphasize edges and textures. The Variance filter replaces the standard deviation for its neighborhood.
- Phase: This filter produces an image that expresses the direction of intensity change (the gradient) in a neighborhood as an intensity value (this filter is a complement of the Sobel filter). The phase filter gives a 3-dimensional relief look to the image -- areas that have no intensity differences are flat, and those with any variation are coded to indicate whether they are brighter or darker than those above it. Generally, the lightest intensities depict vertical transitions to brighter intensities.
Use of Phase filter to locate edges and indicate direction of intensity changes. Note how minor imperfections also became visible in the filtered image.
- Horizontal Edge: This edge filter accentuates the horizontal edges in an image by highlighting pixels with significant intensity differences from those above and below it. It produces an image with just its horizontal edges visible against a flat background. Horizontal Edge filtering is used when horizontal features need to be extracted from an image.
- Vertical Edge: This edge filter accentuates the vertical edges in an image by highlighting pixels with significant intensity differences from those to the left and right of it. It produces an image with just its vertical edges visible against a flat background. Vertical Edge filtering is used when vertical features need to be extracted from an image.
Morphological or nonconvolution filters also work with pixel neighborhoods; however, unlike convolution filters, they do not multiply the neighborhood values by a kernel of filtering coefficients. Instead, a nonconvolution filter works only with the data in the neighborhood itself, and uses either a statistical method or a mathematic formula to modify the pixel upon which it is focused.
The following Morphological filters are provided by Image-Pro:
- Erode: The Erosion filter is a morphological filter that changes the shape of objects in an image by eroding (reducing) the boundaries of bright objects, and enlarging the boundaries of dark ones. It is often used to reduce, or eliminate, small bright objects.
- Dilate: The Dilation filter is a morphological filter that changes the shape of objects in an image by dilating (enlarging) the boundaries of bright objects, and reducing the boundaries of dark ones. The dilation filter can be used to increase the size of small bright objects.
- Open: The Open filter is a morphological filter that performs an erosion, then a dilation. In images containing bright objects on a dark background, the opening filter smoothes object contours, breaks (opens) narrow connections, eliminates minor protrusions and removes small dark spots. In images with dark objects on a bright background, the opening filter fills narrow gaps between objects.
- Close: The Close filter is a morphological filter that performs a dilation followed by an erosion. In images containing dark objects on a bright background, the opening filter smoothes object contours, breaks narrow connections, eliminates minor protrusions and removes small bright spots. In images with bright objects on a dark background, the closing filter fills narrow gaps between objects.
Note - The morphological filters: Erosion, Dilation, Open, and Close are named for their effect on bright objects on a dark field. For example, the erosion filter "erodes" bright objects, the closing filter "closes gaps" between bright objects, and so forth. To obtain a morphological effect upon dark objects on a bright field, use the opposite morphological filter -- e.g., use the dilation filter to do an erosion, use the opening filter to close gaps. etc.
- Top hat: Use this filter to detect and emphasize points, or grains, that are brighter than the background. Available in 3 kernel sizes: click the radio button indicating the kernel size that most closely matches the size of the grains you want to detect.
- Well: Use this filter to detect and emphasize points, or grains, that are darker than the background. Available in 3 kernel sizes: click the radio button indicating the kernel size that most closely matches the size of the grains you want to detect.
- Watershed: Select this filter to separate objects that are touching. The Watershed filter erodes objects until they disappear, then dilates them again, but will not allow them to touch. The Watershed filter will not operate upon True Color images. If you want to separate objects in a True Color image, you must first convert it to Gray Scale.
- Thinning: This filter reduces an image to its skeleton. It operates on a binary basis; pixels are part of an object if their intensity is greater than 127, otherwise, they belong to the background. To identify what objects the Thinning filter will operate upon, it is best to threshold the image before applying the Thinning filter.
- Pruning: Select this filter to eliminate projecting arms from an object.
- Distance: Select this filter to create a distance map of the image.
- Reduce: Select this filter to reduce the objects in an image to a single point or group of points.
- Branch/Endpoints: Use this filter to identify morphological branch and endpoints in an image.
- Sculpt: Use this filter to apply a sculpted effect to the image.
- Background: Select this filter to extract the background from an image. The Background filter works by filtering out objects using a very large filtering kernel. The background image, with objects removed, is placed into a new, untitled image window.
- Distance: The Distance filter is used for showing the distances of pixels within blobs to the outer boundaries of those blobs. After applying the Distance filter, the background will be black (i.e., pixels with values of 0). Only the area within the blobs will have non-zero values (i.e., will be white). The values of each pixel within the blobs will be a count of the shortest distance from the pixel to the edge of the blob. Thus, all pixels along the blob's border will have a value of 1 (since they are 1 pixel away from the edge of the blob), pixels that are a distance of 2 from the border will have the value 2, and so on. This creates a distance map of the image.
- Phase: Select this filter if you want to enhance edges in a manner that expresses the direction of intensity change (the gradient) in a neighborhood as an intensity value (this filter is a complement of the Sobel edge filter). The phase filter gives a 3-dimensional relief look to the image -- areas that have no intensity differences are flat, and those with any variation are coded to indicate whether they are brighter or darker than those above it. Generally, the lightest intensities depict vertical transitions to brighter intensities.
If you are having difficulty separating your objects from other elements within your image, a number of pre-processing techniques are offered to help you enhance object definition.
- Contrast Enhancement: Often, simply increasing the contrast in your image will improve your ability to extract objects more successfully.
- Background Flattening: The Flatten Background command on the Count/Size window's Image menu is used to even out intensity variations in the background of a Gray Scale image (flattening is not applicable to True Color images). When flattening the background, you will be required to describe your object size and color in the Flatten Background dialog box. If your image has lots of objects, or your objects are very large, leaving only small patches of background showing, you may need to set the Background option to specify the color of your objects, rather than the background.
You can also perform background flattening using Image-Pro's Filters command.
- Background Subtraction: The Background Correction command on the Process menu can be used to produce a flat background, and compensate for nonuniform lighting, nonuniform camera response or minor optic artifacts (such as dust specks that mar the background of images captured from a microscope).
To use the Background Correction tools, you must have, or be able to capture, an image of the background light (to produce a background image, capture an image with the slide removed from the stage, or with the optics completely defocused). When the background image is subtracted from your image, areas that are similar to the background will be replaced with values close to the mean background intensity.
Note - Within the Background Correction dialog box, are two correction options: Background Correction and Background Subtraction. If the purpose of the correction is to facilitate object segmentation, use Background Subtraction.
If the purpose of the correction is to obtain accurate density measurements, use Background Correction instead.
Auto-threshold (Count/Size) is an iterative method. It assumes that the gray level histogram is the sum of two normal intensity distributions (two classes): Object pixels and background pixels. The threshold is usually not obvious because the two distributions overlap. The trick is to find where the two distributions intersect (By the way, even when the histogram has a clear valley, the threshold is not necessarily at the bottom of that valley).
For each gray level (t) along the histogram (h(t)), the algorithm calculates the variance of the two portions of the histogram lying on each side of t (v1(t) and v2(t)). It picks the gray level (threshold) that minimizes the sum of the two normalized variances. This variance is sometimes called the "within-class" variance, and can be expressed as:
vw(t) = s1(t)*v1(t)/S + s2(t)*v2(t)/S
s1(t) = Sum(h(i), i=1->t),
s2(t) = Sum(h(i), i=t+1->n),
S = Sum(h(i), i = 1->n),
n = size of histogram.
In practice, instead of minimizing vw(t), the algorithm maximizes the "between-class" variance. It's faster, more complicated to explain, but it's the same exact thing.
One of Image-Pro's most powerful capabilities is its ability to let you perform spatial measurements upon your image, manually or automatically. There are two basic ways to perform measurements within Image-Pro:
- Manually measuring single objects. Using the Measurements command in the Measure menu, you can measure the length of lines or polylines that you define, the area of polygons that you define, and the angles of arcs that you define. The Measurements command also lets you automatically trace and measure the edge of an object or feature in your image. You can measure distances between any two features, and perform tolerance testing using the new features of Image-Pro Plus Version 4.0.
- Automatically counting and measuring multiple objects. Using the tools on the Measure menu, you can collect multiple measurements of multiple objects within a single image. If your objective is to count the number of cells in a sample, and measure the area, roundness or perimeter of these cells, this is the tool to use. Once the objects have been counted and measured, you can use the Count/Size window's Measure menu options to automatically sort and classify the objects by any of the measured characteristics. You can also visualize the classified data by plotting it on a scattergram, or pseudo-coloring the counted objects by class.
- Manually counting and measuring multiple objects. Using the Manual Tag selection on the Measure menu, you can collect multiple measurements of multiple objects within a single image. You may select the number of objects in a class (up to 256) and the number of classes in a single image (up to 16), as well as the color, symbol, and name to identify each class.
Note - The counting and measuring operations will take advantage of your math co-processor if your system is so equipped. If you do not have a math co-processor, and plan to do a lot of work with counting and sizing, you may want to consider having one installed.
When a measurement is made, Image-Pro highlights the measuring outline and assigns a reference number. By default, Image-Pro displays its measurement outlines in yellow, and reference numbers in blue, but if you prefer other colors, you can assign them using the Options button in the Count/Size or Measurements window. Measurements remain on the screen until you close the image or explicitly delete the measurements using the Delete Measurements button.
When you have taken automatic measurements using the Count/Size command, the measurement values are recorded on a data sheet. You can view measurement information by simply double-clicking the measured object within the image.
You can view all current measurements by selecting the Measurement Data command on the Count/Size window's View menu. This will open the Measurement Data window, into which the data sheet for the active AOI or image will be displayed. Measurement data can be saved using the Data to File command on the Measurement Data window's File menu. Measurements are stored in ASCII form (*.CNT). The format for a measurement file is defined in Appendix B, File Format Specifications of the Image-Pro Reference Guide.
Measurement operations are performed in terms of image pixel positions, e.g., the length of a measurement is determined by the number of pixels along the line, the area of an outlined object is determined by the number of pixels within the outline, and so forth.Note - When Image-Pro performs a measurement, the pixels included in the outline are included in the measurement. For example, when you are measuring the area of an object you have outlined, the pixels making up the outline are included in the area calculation.
Image-Pro's pixel-level measurements can be scaled to fit any coordinate system. This allows you to obtain measurements which are reported in terms meaningful to your application. For example, you can calibrate the measurement scale so that one pixel is equal to one foot, or so that five pixels are equal to one foot (or inch, or mile, or micron ). Fractional values are allowed. Image-Pro will express your measurements in terms of that unit. Additionally, if your image contains a measurable object of the unit length, you can calibrate your scale directly from that object, using the Image button in the Spatial Calibration dialog box.
Important - Calibrate your scale before taking your measurements. Once measurements are recorded, their values are not affected by a subsequent change in spatial calibration. For example, if after taking a line measurement of 50 pixels where 1 unit equals 1 pixel, you changed calibration to 1 unit equal to 10 pixels, the first measurement you recorded would remain at 50; Image-Pro will not automatically re-scale it to 5 to after the calibration is changed. You must take the measurement again in order for the new calibration to be reflected.
Once you have set your intensity range selection in Count/Size, go to Count/Size|Select Measurements menu and select the PerArea measurement parameter. Press the "OK" button to accept and then press the Count button to count the objects. Open the statistics table by selecting the View|Statistics menu and observe the row called "Sum" in the table. In the column called PerArea and the row Sum, if found a decimal number. This decimal number multiplied by 100 gives the percent area of objects in you image. By creating any AOI (Area of Interest) and then following the same procedure as above, this will give the area% of objects WITHIN the AOI.
In Image-Pro Plus version 3.0 or later: Go to File, Print, and check the Print Overlay box. If this does not seem to work, try changing the color of your overlay. If the overlay is BLACK, change it to another color. Blue..red.. anything but black. The color of the overlay can be changed in the Count/Size dialog. Go to Measure/Count-Size/Options button/Choose Color button.
Question: How do I measure fluorescence intensity?
Answer: You DON'T! Image Pro Plus can provide Intensity or Density measurements for any image. However, unless the image acquisitions system is properly calibrated, those numbers may not have any useful relationship with the real world.
With the exception of a few special cases, fluorescence is as much an art as an exact science! There are difficulties faced by all dyes, and some that are unique to fluorescent dyes. The following lists cover the highlights of these problems, but are by no means a comprehensive list:
Problems affecting ALL dyes:
- There are often problems involved in getting the dye to its binding site - there may be physical barriers (e.g. membranes, protein folding, etc.) and chemical barriers (e.g. oxidizers, reducing agents, enzymes, hydrophobic/hydrophilic interactions, etc.). Binding of two molecules (through chemical or physical means) is not a constant, measurable event - it is a probabilistic event, which is influenced by environmental factors such as pH, temperature and physical constraint.
- The chemistry of labeling the carrier molecule with the fluorochrome is also a probabilistic event.
- Finally, there are uncertainties in the camera - not every photon that reaches the camera will be converted to a measurable electron.
Problems specific to Fluorescent dyes:
- Fluorescent dyes photobleach! Photobleaching is the process by which the emission intensity of a fluorochrome decays over time. Mathematically speaking, photobleaching is an exponential function of total excitation intensity (over time) and local oxidation environment.
- Although it is possible to measure the total light output by a lamp, it is difficult to accurately track the total amount of light that impacts the specimen (power over time).
- Some samples will have an autofluorescent background that is difficult or impossible to suppress.
- Certain sets fluorescent dyes may experience problems with crosstalk (emission light from one dye showing up on the channel of another dye).
Every time a sample is exposed to excitation light, it is altered to some degree - no two images of the same location will have the same intensity!
The combination of so many random events necessary to producing fluorescent image is nearly impossible to quantify. In particular, it is impossible to compare the fluorescence of different samples or different tissue sections, or sample on different slides - there are just too many variables that cannot be quantified in this process to get reasonable numbers out of such a comparison.
Consider the example of using fluorescence intensity to characterize the effects of two different treatments on a rat's colon. If the treatments are done in vivo you are using two different animals, and therefore must account for all of the possible factors involved in care of the rats (feeding schedules, light/dark cycles, temperature, stress levels, and etc.). Once the rats are sacrificed, you have to account for any differences in time or exact method of sacrifice; also, consider the time necessary to dissect the animals and extract their colons. Are the any differences in the handling of the tissues as they are fixed, embedded and sectioned? Once the sections are back, are there any differences in staining procedure between the samples? If the samples are not mounted on the same slide, does the lamp maintain the exact same level of illumination between slides?
Although many of the variables mentioned in this example can be controlled and quantified - if the rats are kept in cages side by side most of those questions are of little consequence, but what if one rat is not killed on the first attempt? And, other variables cannot be easily quantified at all - Hg lamps are known to fluctuate in intensity, especially near the end of their life span.
With all of the above caveats in mind, it is possible to control enough of the variables with a reasonable degree of confidence to say that one sample has a brighter emission than another. But, you cannot say claim that one is twice as bright as another.
The Good News
There is one way to quantify fluorescence intensity: include an internal standard in your sample that allows you to account for variations in staining efficiency, lamp intensity, etc. There are two methods for including an internal standard:
- Ratio dyes
- Occasionally, fluorescent micro beads have been used
Ratioing compares the changes in intensity of two different emission lines of the same dye as a function of time and environmental change (usually calcium or pH concentration). In this case, the number being compared becomes:
The dye concentration divides out, leaving a unitless ratio. Since you are looking at a unitless ratio, many of the questions about variability of lamp and sample preparation go away: changes in lamp intensity affect the two emission lines identically, and since you are looking at the same sample for both emission lines, there is no difference in preparation.
In the case of fluorescent micro beads, the beads are characterized for efficiency of dye uptake, and the intensity of fluorescence emitted by those beads for a given concentration of dye. In making up a sample, unstained beads are included, so that they will be stained at the same time as the sample. This provides an internal calibration standard that quantifies how much dye actually reached the sample. Using the beads as a reference, it is possible to normalize data from multiple samples and compare the normalized data.
The following is a brief outline of how to go about measuring fluorescence intensity in Image Pro Plus, given all of the previous discussion:
- First and foremost, keep every possible variable constant! This includes the capture system - turn off any auto- settings on the camera or in your camera driver, keep the lamp intensity constant, and always use the SAME optical path.
- Keep sample handling and preparation as consistent as possible.
- Design the experiment around the use or a ratio dye or fluorescent beads.
- Take the time necessary to fully understand and characterize the chosen calibration system.
- Document the chosen calibration method (including dye and bead sources).
There may be situations where you will need to generate your outlines from one image, then superimpose the outlines onto another image to identify object position, or to obtain an average intensity measurement. This is necessary in auto-radiography applications, for example, where cell position and shape is captured in visible light, but cell contents are captured with a different apparatus which does not produce a cell outline.
To measure the intensity within a cell, the outlines are generated by the first image, then superimposed upon the second image. Then, an intensity measurement is performed using the Population Density measurement in the Count/Size command's Measure menu.
Object outlines can also be stored using the Save Outlines command on the Count/Size window's File menu. Outlines are stored to Image-Pro's outline files (.SCL). An outline file contains a list of all the polygonal shapes comprising your outlines. The format of this file is described in Appendix B, File Format Specifications of the Image-Pro Reference Guide.
Stored outlines can be used as input to an external program, or can be reloaded into Image-Pro. A stored outline can be subsequently loaded into Image-Pro for positioning purposes or for additional measuring. Outline files are also an essential component to the population density process (see Population Density Analysis).
Once you have defined your objects, you must choose the measurements you want to take. This is done in the Select Measurements command on the Count/Size window's Measure menu. Image-Pro gives you the following measurement options, and you can select as many as you need. All spatial measurements are reported in the current spatial unit; all intensity measurements are reported in terms of the current intensity calibration.
Angle: Reports the angle between the vertical axis and the major axis of the ellipse equivalent to the object (i.e., an ellipse with the same area, first and second degree moments), where 0° £ Angle° £ 180°. The vertical angle is 0°, unless an offset has been set with the Calibration command.
Area: Reports the area of each object (minus any holes). The area comprised of pixels having intensity values within the selected range is reported unless the Fill Holes option has been enabled. If Fill Holes is enabled, all pixels within the object perimeter are included in the area measurement.
Area/Box: Reports the ratio between the area of each object, and the area of its imaginary bounding box, as determined by Area of Object / Area of Box.
Area (Polygon): Reports the area of the polygon that defines the object's outline.
Aspect: Reports the ratio between the major axis and the minor axis of the ellipse equivalent to the object (i.e., an ellipse with the same area, first and second degree moments), as determined by Major Axis/Minor Axis. Aspect is always ³ 1.
Average Diameter: Reports the average length of diameters measured at 5° intervals around the centroid of each object.
Box Height: Reports the height of the bounding box along the major axis (i.e., the bounding box is the smallest rectangle that completely encompasses the whole object).
Box Length: Reports the length of the bounding box along the major axis (i.e., the bounding box is the smallest rectangle that completely encompasses the whole object).
Box Width: Reports the width of the bounding box along the major axis (i.e., the bounding box is the smallest rectangle that completely encompasses the whole object).
Box X/Y: Reports the ratio between the width (X) and height (Y) of each object's imaginary bounding box, as determined by Box Width / Box Height.
Density Blue: Reports the mean blue value for the measured object in a true color image.
Centroid X: Reports the X-coordinate position of the centroid of the object from the left side of the image.
Centroid Y: Reports the Y coordinate position of the centroid pixel of the object from the top of the image.
Center Mass-X: Reports the X-coordinate position of the centroid of the object based on intensity measurements.
Center Mass-Y: Reports the Y coordinate position of the centroid pixel based on intensity measurements.
Class: Reports the class number to which the object belongs. This value will only be reported if the objects have been previously classified using the Single Variable Class command. If they have not, a Class measurement will not appear on the Measurements data sheet.
Cluster: A cluster is a group of objects defined by an AOI. Cluster reports the number of individual objects contained within the outline.
Clumpiness: Derived from Heterogeneity measurement; The fractions of heterogeneous pixels remaining in an object after an erosion process. It reflects the object texture.
Count (adjusted): Reports the size-weighted object count. Only works when "clean border" flag is turned on.
Diameter (max): Reports the length of the longest line joining two outline points and passing through the centroid.
Diameter (mean): Reports the average length of the diameters measured at two degree intervals joining two outline points and passing through the centroid.
Diameter (min): Reports the length of the shortest line joining two outline points and passing through the centroid.
Feret (max): Reports the longest caliper (feret) length.
Feret (mean): Reports the shortest caliper (feret) length.
Feret (min): Reports the average caliper (feret) length.
Fractal Dimension: Reports the fractal dimension of the object's outline.
Density Green: Reports the mean Green value for the measured object in a true color image.
Heterogenity: Reports the fraction of pixels that vary more than 10% from the average intensity of the object.
Holes: Reports the number of holes inside an object. A "hole" is defined as any contiguous set of pixels within an object that have intensity values outside the selected range for objects. If the Fill Holes option is set, this value will be 0.
Hole Area: Reports the area of holes within an object. A "hole" is defined as any contiguous set of pixels within an object that have intensity values outside the selected range for objects. If the Fill Holes option is set, this value will be 0.
Hole Ratio: Reports the ratio of the object area excluding holes, to the total area of the object, as determined by Area / (Area + Holes Area). Remember, when a Hole measurement is selected, Area is the area of the object less the area of the holes. If the Fill Holes option is set, this value will be 1.
Major Axis: Reports the length of the main axis of the ellipse equivalent to the object (i.e., an ellipse with the same area, first and second degree moments).
Minor Axis: Reports the length of the minor axis of the ellipse equivalent to the object (i.e., an ellipse with the same area, first and second degree moments)
Max Diameter: Reports the length of the longest line that can be drawn to pass through the centroid position and join two points on each object's perimeter.
Min Diameter: Reports the length of the shortest line that can be drawn to pass through the centroid position and join two points on each object's perimeter.
Max Radius: Reports the maximum distance between each object's centroid pixel position and its perimeter.
Min Radius: Reports the minimum distance between each object's centroid pixel position and its perimeter.
Max Density: Reports the maximum intensity or density inside the object.
Min Density: Reports the minimum intensity or density inside the object.
Margination: Reports the distribution of intensity between the center of an object and the edge of the object.
Integrated Optical Density (IOD): Reports the average intensity/density of each object. This value will be expressed in terms of the current intensity/density mode and calibration.
Perimeter: New measurement to report the length of the outline of each object. When holes are outlined, the perimeters of the holes are added to the perimeter of the object.
Perimeter2: Old measurement from version 3.0. Faster but less accurate than current perimeter measurement. Reports the length of the outline of each object. When holes are outlined, the perimeters of the holes are added to the perimeter of the object.
Perimeter (Convex): Reports the perimeter of the convex outline of each object.
Perimeter (Ellipse): Reports the perimeter of the ellipse surrounding the outline of each object.
- Perimeter (Ratio): Reports the ratio of the convex perimeter to the perimeter of the outline of each object.
PerArea: Reports the ratio between the area of the counted object to that of the entire area. The ratio is determined by (Object Area/Total Area) where Total Area is the area of the active image or AOI (whichever was in effect when the measurement was taken).
Radius Ratio: Reports the ratio between Max Radius and Min Radius for each object, as determined by Max Radius / Min Radius.
Density Red: Reports the mean red value for the measured object in a true color image.
Roundness: Reports the roundness of each object, as determined by the following formula:
(perimeter2) / (4 * p * area). Circular objects will have a roundness = 1; other shapes will have a roundness > 1.
Size Count: Reports the count of multiple objects of varying sizes in multiple frames.
Size (length): Reports the feret diameter (caliper length) along a major axis of the object.
Size (width): Reports the feret diameter (caliper length) along a minor axis of the object.
Std. Dev. Density: Reports the standard deviation of density or intensity inside the object.
Once you have identified the measurements you want to take, you can set measurement criteria that will determine which objects Image-Pro includes in the count.
For example, you can instruct Image-Pro to include only objects larger than a certain size. This is done by establishing a valid range (i.e., specifying minimum and maximum values) for each measurement using the Set Ranges command in the Measure menu. If the object's measurement is within this range (min and max, inclusive), it will be included in the count. Objects with values outside the range are ignored.
Once you have identified your objects, selected your measurements and tailored the count with the options you need, you are ready to initiate the count itself. To do this, click the Count button in the Count/Size dialog box.
Image-Pro will analyze your image, and will outline and measure the objects it finds meeting your selection criteria. When it is done measuring, it will display the object outlines, and write all the requested measurements to the measurement data sheet.
You can view the measurements for an individual object by double-clicking the object in the image. This produces a pop-up window that contains the measurements for the selected object. The measurement data sheet, which is a table of all the measurements, can be viewed by selecting the Measurement Data command in the View menu.
Using the Count/Size command on the Measure menu you can count and measure multiple objects automatically. Once the objects have been counted and measured, you can use the Count/Size window's Measure menu to automatically classify them by any of the measured characteristics.
You can also visualize the data by plotting it using the Count/Size window's View menu options, or color the counted objects by class using the Auto Classification command on the Count/Size: Measure menu.
A new feature of Image-Pro Plus version 4.0 allows you to sort your counted objects according to area or other measurements. Use the Sort Objects selection on the Measure menu to generate a new image of your objects in sorted order.
Image-Pro offers several additional options that let you tailor your count to your needs, including how partial objects will be treated, and how objects will be labeled.
These miscellaneous options are selected using the Options button in the Count/Size window:
Smoothing: This option lets you set a factor that determines whether or not the perimeters of the counted objects will be smoothed. A factor of 0 indicates that no smoothing should be done. Values greater than 0 turn smoothing on, and indicate the degree of smoothing that should take place. If perimeter and roundness are critical measurements to your analysis, you may want to use this option. Bear in mind that smoothing will lengthen the time it takes to perform your count, so you will want to use this option only when it is truly necessary.
Clean Borders: This option determines whether partial objects that lie at the border on an image should be included in the count (partial objects can skew your results). If Clean Borders is selected, these partial objects will be ignored.
Outlines: This option determines whether outlines of the counted objects will be shown or not. If objects are to be outlined you can select one of several outline formats: perimeter, elliptical, filled or class. When Outline is selected, the object's perimeter is outlined. When Ellipse is selected, the object's equivalent ellipse (an ellipse with the same area, first and second degree moments as the object) is displayed. The Ellipse option is particularly meaningful in grain-counting experiments, because it identifies an object's ideal domain, from which binding sites can be identified. The Filled option shows counted objects in solid color, and the Class option colors the objects by category (see Visualizing Your Measurement Data ). This option also allows you to select the color in which you want the outlines displayed. Dot marks each counted object with a small cross hair positioned in the center of each object's bounding box.
Label: This option determines whether an object's unique numeric label should be displayed following the counting process, and what color should be used to display it. The displayed labels allow you to visually match objects with your results, and should rarely be turned off. The only times you may want to turn labeling off are to eliminate screen clutter or inspect the details of a particular outline.
Object Limits: Up to 16,000 objects can be included in a single count. If your image contains more than 16,000 objects, consider using AOIs to process the count in a series of small batches. Image-Pro also has an internal limit of 250,000 object "segments." A counted object is built of segments, which are horizontal, single-pixel "slices" of the object. Each segment is represented internally by its beginning and endpoint coordinates.
Objects containing lots of fissures or holes will require many segments to describe their shape. If you have many such objects, the internal limit of 250,000 segments could be exceeded. Consider using AOIs to process the image in a series of small batches if this limit is encountered.
Outline: The Outline option in the Count/Size Options dialog box can outline object perimeters comprised of up to 4096 vertices. If your object has a very, very large, irregular perimeter, you may exceed this limit and its outline will not be displayed correctly (all measurements taken for the object are correctly reported, however). To display an outline of a very, very large object, select either the Filled or With Holes outline styles.
For counting purposes, objects are identified by their intensity (monochrome images) or color (True Color-class images). Therefore, it is best to begin with an image that contains objects that are clearly distinguishable from the background, and have an intensity range/color different from other elements in the image. Because many images do not initially fit such ideal conditions, there are a number of "pre-processing" steps you can take to correct such deficiencies (pre-processing is discussed a little later in this section).
The first step in performing a count is to identify the objects you want to include in your count. This is done by specifying the range of intensities or colors that uniquely identifies your objects. The way in which you do this first step depends upon whether your image is Gray Scale or True Color.
Note - If your image is a Palette-class image, it must first be converted before the Count/Size command can be used with it.
If you are working with a gray scale image, selecting your object's intensity range in a Gray Scale image can be done manually, or automatically. To manually specify object intensity, use the Manual option and the Select Range button. With your image on the screen, move the range markers until all your objects are highlighted. If you highlight a few extraneous objects in addition to the ones you want, don't worry — they can be manually removed from the object group after the count using the Hide option in the Object Window command. However, if you find that your objects can't be highlighted without including numerous unwanted elements, you will need to use one of the pre-processing tools to increase object differentiation or eliminate unwanted noise. See Pre-Processing.
To have Image-Pro automatically set the intensity range that defines your objects, you can use its Automatic option. When a count is performed with the Automatic option, Image-Pro will analyze your image, calculate the intensities distinguishing objects from background, and establish the intensity range based upon the objects that it finds. When running a count with the Automatic option, you must be sure to set the Bright Objects or Dark Objects option to describe your objects.
If you are working with a True Color Image, selecting your object's color range is done by identifying an AOI that encompasses the colors of your objects. Selecting a color for counting purposes is essentially performed in the same way as extracting a set of colors using the Segmentation tool -- that is, you select a set of colors that separates certain features (in this case, objects to be counted) from the rest of your image. To confirm that your color selection is extracting just the objects you want, use the Create Image button to view your image with all but the selected colors grayed out. Refine your selection by adjusting the color ranges, until just the objects you want to count are visible.
Before working with the data sheet, you should take a moment to review the display to make sure you are satisfied with the objects that have been extracted — you may want to eliminate extraneous objects, separate clusters that have been counted as a single object, or combine separate outlines into one. On the Count/Size: Edit Count/Size Edit Menu menu, Image-Pro gives you a number of tools that let you edit and finalize your count.
Draw/Merge Objects: This option lets you manually outline an object that was not included in the count, or combine two objects so that they are counted as one.
To manually include an outline, select Draw/Merge then draw a polygon that traces the object, using any of the standard AOI tools: rectangular, elliptical or freeform (you can even use the Freeform tool's Auto Trace feature to automatically trace an edge.) When you have finished drawing the polygon, the specified measurements for that shape will also be added to the data sheet.
Note - You can draw a polygon that defines an object that doesn't visibly exist in your image. This is usually done to define a region from which population density can be calculated.
To combine two closely positioned objects into a single object, simply draw a narrow polygon that connects (not outlines) the two existing objects.
Merging many objects in such a manner might be done to develop area outlines for population density analysis (see Population Density Analysis).
Split Objects: This option lets you manually divide clusters into single objects. Dividing is done drawing a division line between the objects you want to separate.
After separation, the measurement data sheet will be updated to reflect the additional object, and the measurements of the original object will be adjusted to reflect the remaining object.
Auto Split: You can also use the Auto Split command to instruct Image-Pro to analyze all existing outlines and automatically split any clustered objects it finds. Of course, not all clustered objects can be separated with Auto Split; in general, circular objects with minimal overlap work best. Use the following criteria for determining whether your objects are clustered in a way that can be easily separated by the Auto Split operation:
¨ Individual objects within the cluster should be convex-shaped. An object is considered convex if all lines joining two points of the outline fall within the object.
¨ Objects should not overlap each other by more than 30%.
¨ The intersection of two overlapping objects should be identifiable by two concave points.
¨ Object outlines should be smooth enough to readily distinguish a concavity created by an overlap from a concavity that is simply part of the object.
Note - Image-Pro splits objects with a straight line. It does not attempt to reconstruct the missing or hidden portions of an object.
If the Auto Split command does not yield satisfactory results, try using the Watershed Split. This method does not rely on object concavities to determine lines of separation. Instead it erodes an object until it disappears, then dilates it back to its initial size, but does not allow it to touch its neighbors.
Watershed Split: Use the Watershed Split to automatically analyze every counted object and split clusters using the Watershed separation technique. The Watershed method erodes objects until they disappear, then dilates them again such that they do not touch.
The Watershed Split command may be more effective than the Auto-Split method if your objects are not convex.
You may remove an extraneous object from your count by using the Toggle Objects On/Off feature from the Count/Size : Edit menu. When an object is hidden, its outline and label are removed from the display and its measurements are eliminated from the data sheet. Deactivated measurements are also excluded from global statistic, classification and visualization operations. To permanently remove hidden objects, choose Delete Hidden Objects from the same Count/Size:Edit menu.
When a count operation is performed, the requested measurements (those selected with the Select Measurements command from the Count/Size : Measure menu) for all counted objects are written to the measurement data sheet. This data sheet can be viewed by selecting the Measurement Data command from the Count/Size : View menu.
The data sheet contains only values for the requested measurements; if you want to incorporate additional measurements in your data sheet you will need to select them, then re-measure the outlines by clicking the Measure button (keep the original measurements selected too, if you want them to appear in the data sheet).
Statistics, such as minimum, maximum, mean and standard deviation can be viewed using the Statistics command on the View menu. A set of these statistics is produced for each measurement you have selected.
Measurement data can be stored to a file using the Data to File command on the Count/Size window's File menu, or on the Measurement Input/Output tab dialog. Data can be stored in ASCII or LOTUS 123ä WK1 format.
Use the Measurements, Thickness option in Image-Pro. You can choose among three ways of calculating thickness: along horizontal lines, along vertical lines and along lines that follow the curvature of the outlines. If your layer is not flat (i.e. the medial axis is globally curved), you should chose the third option. In the third option, the thickness is calculated by finding the shortest distances between the two outlines, at regular intervals along the outlines. The interval depends on the length of the outlines and is such that the program calculates up to 200 distances or so. Once all the shortest distances are known, Image-Pro keeps the minimum, maximum and average distances.
This method gives very similar results to measuring distances perpendicularly to the axis of the outlines, but is less prone to sampling errors in very convoluted outlines.
The manual measuring tools are accessed using the Measurements command on the Measure menu. The manual tools are useful for obtaining individual measurements, and they are the only way to obtain straight-line length and thickness measurements. You can define features that have measurements of their own (the length of a line, for example) or take measurements between two existing features (i.e. distance, angle, or thickness).
The following tools are used to create the primary features:
Selection: This button is used to select existing features and/or measurements, i.e. to move or delete them. You may select more than one feature by holding down the key while you use the mouse to click on the feature.
Remove: This button is used to remove all of the currently selected features or measurements from the image. All related measurements in the Measurement tab and the corresponding row(s) in the Features tab will be removed.
Point: This button is used to create a point feature on the current image.
Straight Line: This button is used to create a straight line feature on the current image. (This is the equivalent of the Length tool in previous versions of Image-Pro Plus.)
Best Fit Line: This button is used to create a straight line that best fits several points on the current image. Click on the image to add up to 1000 points, and double-click to end the list of points. A setting on the Options page determines a user-defined limit to the number of points and the feature will be added when this limit is reached. For instance, to draw a two-point line (with two clicks) this option could be set to a user limit of 2. The end points of the line will be the point where the line is perpendicular to the first and last points.
Circle: This button is used to create a circle feature on the current image.
Best Fit Circle: This button is used to create a circle that best fits several points on the current image. Click on the image to add up to 20 points, and double-click to end the list of points, creating the best-fit circle. A setting on the Options page determines a user-defined limit to the number of points and the feature will be added when this limit is reached.
Best Fit Arc: This button is used to create an arc that best fits several points on the current image. Click on the image to add up to 20 points, and double-click to end the list of points. The points of the arc will need to be ordered, i.e. clicked in order from the beginning to the end of the arc. A setting on the Options page determines a user-defined limit to the number of points and the feature will be added when this limit is reached.
Rectangle: This button is used to create a rectangle feature on the current image.
Polygon: This button is used to create a polygon feature on the current image. This will be created using the current trace/wand tool, and will always yield a closed figure. (This is the equivalent of the Area tool in previous versions of Image-Pro Plus.)
Trace: This button is used to create a trace on the current image. This will be created using the current trace tool, and will always yield a open figure. (This is the equivalent of the Trace tool in previous versions of Image-Pro Plus.)
The automatic tracing tool works by following an edge of significant contrast. When you start a trace, select the point at which you want the trace to begin by clicking your mouse button. Then, click a second point along the edge to indicate the direction that Image-Pro should begin following the edge. If Image-Pro gets lost during its trace (loses the edge), it will stop. If it has wandered beyond the edge of your object, you can press to back up the trace to the edge, then manually lead the trace by moving the cursor to the next significant point along the boundary and clicking the left mouse button.
Successful tracing is dependent primarily on how well differentiated your object is from the background. If there is good contrast between it and the pixels that surround it, your automatic traces will perform very well. Edges that have low contrast from the background, or have lots of competing edges intersecting them, will be interrupted more frequently.
These controls let you fine-tune Image-Pro's edge detection mechanism, used by the Trace and Freeform tools.
Magic Wand: The magic wand tool makes it easier to outline an irregular AOI. Simply place the wand cursor inside the area that you want to trace, and click the left mouse button once. The magic wand will automatically trace the outline of the object(s) based on the color similarities or difference of intensity ranges between the pixel under your cursor, plus or minus a specified tolerance interval.
Threshold: This value (from 1 - 10) describes the level of contrast distinguishing the edge you want to track from its surrounding elements. If there is low contrast, this value should be set to a low number.
Smooth: This value (0-9) specifies the amount of post-filtering of the outline you want. 0 = no smoothing, 9 = high degree of smoothing.
Noise: This value (1 - 6) specifies the number of pixels Image-Pro advances when moving to the next edge position. A larger value here results in a smoother outline (it won't follow every nook and cranny) and faster trace, but may cause it to get lost more frequently. Specifying values over 3 or 4 generally causes the Trace to overshoot curves along your edge.
Speed: This value (0 - 5) specifies the rate at which the outline will be drawn. A small value here will slow down the trace function. You might do this to make it easier for you to watch the trace as it progresses.
The following measurement tools are available to take measurements between features created with the feature tools:
Distance Measurement: This button creates a measurement of the distance between two user-selected features.
Angle Measurement: This button is used to create two lines and do an angle measurement between these two lines. Note that this tool is different from the five other measurement tools in that rather than selecting two features for the measurement, two features are created and then the measurement derived from them.
Angle Measurement: This button creates a measurement of the angle between two user-selected line features. (This is the equivalent of the Angle tool in previous versions of Image-Pro Plus.)
Horizontal Thickness: Adds a thickness measurements between two primarily horizontal lines or traces.
Vertical Thickness: Adds a thickness measurement between two primarily vertical lines or traces.
Curve Thickness: This button creates a measurement of the minimum or maximum distance between two user-selected traces in any direction.
Another option to identify objects in your image is to use the Manual Tag option from the Measure menu. Manual Tag allows you to select points in an image, and assign them to a specific class.
You can define up to 16 classes of objects for a single image, and assign each class a name, color, and identifying symbol. Image-Pro Plus automatically keeps track of the points as you select them. You can display information about each class including minimum, maximum, mean, standard deviation, and total by using the Manual Tag : View : Class Stats Manual Tag View Menu menu.
Manual Tag : Options allows you to see the x and y position, intensity, and class of each tagged object in the image.
Manual Tag measurement information can be stored using the Data to File command on the Manual Tag : File menu. Data and statistics are stored in an ASCII file (assigned the extension .CNT), which contains location information about the different markers. A portion of a .CNT file appears below.
A Manual Tag file is created when you store your class and/or tag marker information in the Manual Tag selection from the Measure menu. A *.TAG file is created using the Save Points command on the File menu in the Manual Tag dialog box.
A *.TAG file is an Image-Pro file that contains the class and marker information that is to be applied to the objects in an image. This data is not in ASCII format. Users should not attempt to modify a *.TAG file.
When Image-Pro Plus is counting objects in the Count/Size feature you will notice that the numbers seem to be randomly set to objects.
Actually what you are seeing is that Image-Pro Plus is reading the image from the left most and top most corner line by line.
When it encounters an object to be counted it gives it the object number 1 and then as it progresses with this scan it then gives each encountered object the next sequential number.
To see this property of Image-Pro Plus first open Spots.tif then create 3 AOI's on the image and count. Then create a 4th AOI somewhere between the other AOI's and redo the count you will notice that numbers will have jumped from one object to another.
Note: The numbering of objects can also be effected by whether or not you are filtering or ignoring objects.
Measurement calibration is possible using reticules available from many Image-Pro dealers and microscope suppliers and well as companies such as Edmund Scientific and Fisher Scientific. Kodak has a variety of targets available for calibration of non-microscopic optical systems. For larger objects you should not neglect the possibility of imaging a set of accurate rulers, if they are flat enough to lie in the same optical plane as the objects.
There are many kinds of calibration standards available, including targets for calibrating angle, distance, intensity, linearity, and the spatial frequency response (Modulation Transfer Function or the Optical Transfer Function - MTF and OTF). The choice of which standard to use depends on what measurements you are making.
You should calibrate your measurements of importance both at the center of your imaging field and at the edges to ensure that your optical system is reasonably flat and undistorted. Total system precision is limited by the maximum of the smallest resolution of the system (how large is a pixel, how many gray scales can be distinguished), the limit of optical resolution, and optical distortions. System accuracy is limited by the sum of these resolution limitations and the base accuracy of your calibration standard as listed by the manufacturer. (Accuracy = adherence to an absolute standard, Precision = repeatability.)
A note about calibrating X and Y axis: No matter what optical system you use, as long as the image is digitized by a camera, a frame grabber, or a scanning device, you have to assume that the digitization process does not have a one-to-one aspect ratio. If that is the case, you will have to calibrate both X and Y axis. Image-Pro allows you to calibrate both axis, or to calibrate one axis and set the aspect ratio. Once calibrated, the program will give you correct spatial measurements regardless of the direction of measurement. Calibration and calibrated measurements are also covered extensively in Media Cybernetics software manuals.
Calibration markers are scaled to true size when placed on the image. Users can not create a true size marker without first performing a true calibration. Since the calibration procedure allows for both creating a calibration line on the image or a numerical input of pixels-to-units ratio, the user can create a calibration that is not compatible with the "true" image calibration. This is what's happening in this case. The calibration has been entered numerically which is not the "true" calibration and when the marker is placed onto the image, the white part of the marker background is so large that it covers the whole image. This is why the image is turning white. A large portion of the marker is completely covering the image and turning it white. By reducing the number of pixels per unit to a "true" calibration level, the marker will be seen on the image.
The Saptial Calibrations dialog offers the ability to place a calibration marker on the image, which is useful for publication, since it easily documents the scale of objects in the image. However, many people find that the calibration marker is only partially visible (or completely invisible) after it is burned into the image.
This is because the calibration marker is burned in as a set of 1 pixel wide lines. One pixel wide lines are used because they eliminate the question of "where is the edge" when using them to calibrate the image again. The lines have not vanished, they have merely been hidden. With the increasing use of mega pixel digital cameras, many people's image are being automatically scaled down to 50% or even 25% of full size in order to display the entire are of the image on screen. Image-Pro reduces the size of an image on screen by only displaying every other row and every other column of pixels (for a 50% zoom). If the burned in calibration marker lines happen to fall on one of the hidden rows or columns, it will be hidden. These hidden lines will become visible if the image is zoomed to 100% or higher.
With respect to spatial calibration, the aspect ratio reflects the relationship between the length of the vertical and horizontal axes in your image, and is expressed as X/Y. Aspect ratio is also calibrated using the Calibration command. If your camera's aspect ratio is not equal to your video card's aspect ratio, an image of a square object will not appear square when viewed on your display. To correct for this inconsistency, you can calibrate the aspect ratio from a reference square within an image.
Note - Camera/video card inconsistencies are not the only reason a square might not appear square on your display. It might simply be a misadjustment of your monitor's Vertical Size control.
Your Product Serial Number is printed directly on your Hardware Protection Key and can also be found on the ‘About’ dialog box. This can be launched by selecting “About <Product Name>” from the Help Menu from inside of the product.