Generalizing the Hough transform to detect arbitrary shapes

• Published in: Pattern recognition Vol. 13; no. 2; pp. 111 - 122
• Main Author: Ballard, D.H.
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 1981
• Subjects: Hough transform; Image processing; Parallel algorithms; Pattern recognition; Shape recognition; Hough transform; Pattern recognition; Image processing; Parallel algorithms; Shape recognition
• ISSN: 0031-3203; 1873-5142
• DOI: 10.1016/0031-3203(81)90009-1

The Hough transform is a method for detecting curves by exploiting the duality between points on a curve and parameters of that curve. The initial work showed how to detect both analytic curves (1,2) and non-analytic curves, (3) but these methods were restricted to binary edge images. This work was generalized to the detection of some analytic curves in grey level images, specifically lines, (4) circles (5) and parabolas. (6) The line detection case is the best known of these and has been ingeniously exploited in several applications. (7,8,9) We show how the boundaries of an arbitrary non-analytic shape can be used to construct a mapping between image space and Hough transform space. Such a mapping can be exploited to detect instances of that particular shape in an image. Furthermore, variations in the shape such as rotations, scale changes or figure ground reversals correspond to straightforward transformations of this mapping. However, the most remarkable property is that such mappings can be composed to build mappings for complex shapes from the mappings of simpler component shapes. This makes the generalized Hough transform a kind of universal transform which can be used to find arbitrarily complex shapes.