bottomHat

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

Use this function to detect small dark regions in an image or selection. The bottom-hat transformation also known as "well" or "rolling ball" works by subtracting the original image from the result of the Close.operator. The shape and size of the neighborhood pattern which could be interpreted as the "brim of the hat" is selected with the Probe parameter.

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.

Iterations

A positive integer specifying how many times the operation will be applied.

Probe

An enumerated integer that describes the shape and size of the kernel used in the operation. The value is determined as a combination of four basic shapes constructed of 3 pixels:

PR_VBAR=1 – vertical bar

PR_BKSLASH=2 – diagonal bar (top left – bottom right)

PR_HBAR=4 – horizontal bar

PR_FWSLASH=8 –diagonal bar (bottom left – top right)

The following frequently used shapes represent combinations of the basic shapes:

PR_CROSS=5 – cross 3x3

PR_DCROSS=10 – diagonal cross 3x3

PR_SQUARE=15 – square 3x3

You can also assign one kernel of size 5x5:

PR_CIRCLE=16 – circle 5x5

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")

genimpulse (1,1,200,50)

tophat(1,101,PR_CROSS,1)

subIm(1,101,102,0)

bottomhat(102,101,PR_CROSS,1)

addIm(102,101,2,0)