threshUnimod
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val = threshUnimod ( integer Input, integer Output, integer Channel,
   [, integer Invert =0 ] )  

Use this function to automatically to automatically separate objects of interest from the background based of the assumption of the unimodal distribution of an image histogram. The functions works by setting the threshold range at the mean intensity value plus and minus three standard deviations.
The function creates a binary output image and returns a calculated threshold.

Parameters
 
Input  
 
An integer between 0 and 116 specifying the input image frame number. A value of 0 represents the DMA memory buffer of the video device. Values in the range of 100-116 correspond to hidden frames.  
 
Output  
 
An integer between 1 and 116 specifying the output image frame number. Values in the range of 100-116 correspond to hidden frames.  
 
Channel  
 
An enumerated integer specifying the color channel that will be used for histogram analysis and thresholding. Must be one of the following values:  
 
TH_LUMINANCE=0 – separate the objects of interest based on the intensity distribution.  
TH_HUE=1 – separate the objects of interest based on the color pigment distribution.  
TH_SATURATION=2 - separate the objects of interest based on the color saturation distribution.  
 
This parameter is disregarded for grayscale images.  
 
Invert  
 
An optional boolean integer that defines if the foreground range should be inverted. Must be one of the following values:  
 
FALSE=0 – normal mode of thresholding. The pixels whose values fall within the range between the calculated threshold levels will be treated as foreground ones, while the pixels with values outside the range will be treated as background ones.  
TRUE=1 – inverted mode of thresholding. The pixels whose values fall within the range between the calculated threshold levels will be treated as background ones, while the pixels with values outside the range will be treated as foreground ones.  
Default value: FALSE  

Return value

A threshold level calculated from the histogram analysis and used for thresholding.  

Error flags
 
ERR_OK  
 
The flag set if successful.  
 
ERR_FAILED  
 
The flag set if failed.  

Example
 
This set of statements continuously captures an image and binarizes it using the unimodal thresholding:  
 
do  
grabim(110)  
threshUnimod(110,1,TH_LUMINANCE,TRUE)  
loop  
 
Remark

The outcome of this function is affected by the Histogram Preferences. Use setHistAttr to set the desired Sampling of the histogram and specify if the black or white pixels should be ignored in the histogram analysis.