 | Threshold Image Controls |
Main Tab
The following controls are available on the Main tab.
| Control Name |
Description |
| Look For |
Specifies the type of objects to search for in the image. The following options are available:
- Bright Objects—When selected, the step counts bright pixels whose intensity values range from Lower Value to 255.
- Dark Objects—When selected, the step counts dark pixels whose intensity values range from 0 to Upper Value.
- Gray Objects—When selected, the step counts gray pixels whose intensity values range from Lower Value to Upper Value.
|
| Method |
Specifies the type of threshold to use. The following options are available:
- Manual Threshold—Use this method when you want to determine the upper and lower threshold values manually.
- Automatic Threshold: Clustering—Use this method as a starting point. This method is appropriate for most images, but if
the image requires more specialized thresholding, select another automatic thresholding method.
- Automatic Threshold: Entropy—Use this method when you are inspecting an image that contains very small objects of interest, such as
small cosmetic defects.
- Automatic Threshold: Metric—Use this method when the object of interest and the background contain a comparable number
of pixels.
- Automatic Threshold: Moments—Use this method for images that have poor contrast.
- Automatic Threshold: InterVariance—Use this method when the object of interest and the background contain a comparable number
of pixels.
- Local Threshold: Niblack—Use this method for images that contain non-uniform lighting conditions.
- Local Threshold: Background Correction—Use this method for images that contain non-uniform lighting conditions. Background correction also helps reduce noise in large, empty areas.
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Note Refer to the NI Vision Concepts Manual for more information about automatic thresholding methods. |
|
| Histogram |
Displays the number of pixels at each grayscale intensity in the region of interest. The x-axis represents the grayscale intensities, and the y-axis represents the number of pixels. |
| Lower Value |
Range of intensity values for those pixels you want to consider as objects. When looking for bright objects, all pixels whose values range from Lower Value to 255 are considered object pixels. Lower Value can be set to a constant or to the value of a previous measurement. |
| Upper Value |
Range of intensity values for those pixels you want to consider as objects. When looking for dark objects, all pixels whose values range from 0 to Upper Value are considered object pixels. Upper Value can be set to a constant or to the value of a previous measurement. |
| Lower Limit |
The lower boundary of the threshold range for manual thresholding. For automatic thresholding, Lower Limit displays the threshold value computed by the selected automatic thresholding method. |
| Upper Limit |
The upper boundary of the threshold range for manual thresholding. For automatic thresholding, Upper Limit displays the threshold value computed by the selected automatic thresholding method. |
| Kernel Size |
The size of the area around each pixel used to compute the average intensity value for the pixel when using a locally adaptive threshold. Kernel Size is typically equal to the size of the object you want to isolate using the threshold. Kernel Size is only available for local thresholding methods.
- ROI Size—Indicates the size of the current region of interest.
 |
Tip You can determine the approximate size of an object in your image by drawing a region of interest around the object. ROI Size displays the value of the last ROI drawn. Click the  Apply ROI button to set Kernel Size equal to ROI Size. |
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| ROI Size |
Indicates the size of the current region of interest.
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Tip You can determine the approximate size of an object in your image by drawing a region of interest around the object. ROI Size displays the value of the last ROI drawn. Click the Apply ROI button to set Kernel Size equal to ROI Size. |
|
| Deviation Factor |
Determines the sensitivity of the Niblack thresholding algorithm. Values range for 0 to 1, with 0 being the most sensitive to noise. This control is available only for the Local Threshold: Niblack thresholding method. |