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These filters attempt, through the use of kernels, to detect edges in the image and change the image so that these edges are enhanced, while the rest of the image is grayed out.

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Filter dialog. Edge detection

There are four edge detection filters, all with the same interface and options, in which the user chooses a threshold in the range 0-255, and the possibility compare the results by ticking the compare check box:

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Sobel filter example

SOBEL

The Sobel filter detects the horizontal and vertical edges separately on a grayscale image. Colour images are converted to RGB gradations. The result is a transparent image with black lines and some remains of colour.

ROBERTS

The Roberts filter is suitable for detecting diagonal edges. It offers good performance in terms of location. The major drawback of this filter is its extreme sensitivity to noise and therefore has poor detection qualities.

PREWITT

The Prewit filter detects edges in all directions as it consists of 8 kernels that are applied over the image pixel by pixel.

FREI-CHEN

The Frei-Chen filter processes the neighbouring pixels as a function of their distance from the pixel that is being evaluated. The result is that edges in all directions are detected.

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