Generalized Hough transform

Hough transform was originally proposed to detect circles in an image. It was later improvised to detect all parameteric shapes. The procedure is to find imperfect instances of objects within a certain class of shapes by a voting procedure. The voting is carried out in parameter space from which the object candidates are obtained as local maxima in accumulator space. This project further extends the algorithm to detect any arbitrary, non-parameteric shapes with different scaling. It uses gradient information around the centroid of the non-parameteric shape to accumulate bin array. Thresholding the bin array gives the centroid of detected shape.

Block diagram

Block diagram
Block diagram

Non-parameteric shape

Shape to be detected
Shape to be detected

Input

Input image with salt and pepper noise
Input image with salt and pepper noise

Output

Detected image
Detected image

Reference

Generalizing the Hough transform to detect arbitrary shape, DH Ballard (1981)

Author

Anurag Gupta is an M.S. graduate in Electrical and Computer Engineering from Cornell University. He also holds an M.Tech degree in Systems and Control Engineering and a B.Tech degree in Electrical Engineering from the Indian Institute of Technology, Bombay.