bottomHatKernel

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)