bottomHatKernel
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bottomHatKernel ( integer Input, integer Probe, integer Output, integer Iterations )

Use this function to detect small dark regions in an image or selection. The top-hat transformation works by subtracting the original image from the result of the
close operator. A neighborhood pattern is supplied to the function as a grayscale or binary image with pixel values set to 1s for active elements of the kernel and to 0s for elements to be ignored.

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.  
 
Probe  
 
An integer between 1 and 116 specifying the frame number of the grayscale or multiphase image that contains the structuring element for the operation. Values in the range of 100-116 correspond to hidden frames.  
The size of the kernel in each dimension must not exceed 2*Overscan+1. The Overscan setting is defined in ImageWarp Preferences.  
 
Output  
 
An integer between 1 and 116 specifying the output image frame number. Values in the range of 100-116 correspond to hidden frames.  
 
Iterations  
 
A positive integer specifying how many times the operation will be applied.  
 
Error flags

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

Example

This set of statements adds an impulse noise to a sample image and then removes it by using the TopHat operator followed by BottomHat.  
 
setColorSpace(CS_RGB)  
setCurDir ("samples")  
loadIm (1,"sample14.iwd")  
toGray(1,1)  
genimpulse (1,1,200,50)  
setCurDir ("scripts")  
loadIm (2,"circle7.tif")  
tophatkernel(1,2,101,1)  
subIm(1,101,102,0)  
bottomHatKernel(102,2,101,1)  
addIm(102,101,3,0)