The circle Hough Transform (CHT) is a basic feature extraction technique used in digital image processing for detecting circles in imperfect images. The circle candidates are produced by “voting” in the Hough parameter space and then selecting local maxima in an accumulator matrix.

In this video I explain how Circle Hough Transform works, by creating an accumulator for every edge detected (using Canny algorithm) in the original image. The accumulator corresponds always to a specific radius size, therefore it only works for circles with this size. For new radius, a new accumulator should be computed. The algorithm was based on the Wikipedia (https://en.wikipedia.org/wiki/Circle_Hough_Transform) adapted for a single radius, because in the original algorithm, all radius are computed.

The source code used to create the animations is available at https://github.com/tkorting/youtube/tree/master/how-circle-hough-transform-works

The slides are available at https://prezi.com/mol2d1rmbpwi/?utm_campaign=share&utm_medium=copy

Download free remote sensing images at http://www.dgi.inpe.br/catalogo

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