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Journal ArticleDOI

A survey of the Hough transform

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TLDR
This survey will provide a useful guide to quickly acquaint researchers with the main literature in this research area and it seems likely that the Hough transform will be an increasingly used technique.
Abstract
We present a comprehensive review of the Hough transform, HT, in image processing and computer vision. It has long been recognized as a technique of almost unique promise for shape and motion analysis in images containing noisy, missing, and extraneous data but its adoption has been slow due to its computational and storage complexity and the lack of a detailed understanding of its properties. However, in recent years much progress has been made in these areas. In this review we discuss ideas for the efficient implementation of the HT and present results on the analytic and empirical performance of various methods. We also report the relationship of Hough methods and other transforms and consider applications in which the HT has been used. It seems likely that the HT will be an increasingly used technique and we hope that this survey will provide a useful guide to quickly acquaint researchers with the main literature in this research area.

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Book

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References
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Journal ArticleDOI

Use of the Hough transformation to detect lines and curves in pictures

TL;DR: It is pointed out that the use of angle-radius rather than slope-intercept parameters simplifies the computation further, and how the method can be used for more general curve fitting.
Journal ArticleDOI

Generalizing the hough transform to detect arbitrary shapes

TL;DR: It is shown how the boundaries of an arbitrary non-analytic shape can be used to construct a mapping between image space and Hough transform space, which makes the generalized Houghtransform a kind of universal transform which can beused to find arbitrarily complex shapes.
Journal ArticleDOI

The Adaptive Hough Transform

TL;DR: This correspondence illustrates the ideas of the Adaptive Hough Transform, AHT, by tackling the problem of identifying linear and circular segments in images by searching for clusters of evidence in 2-D parameter spaces and shows that the method is robust to the addition of extraneous noise.
Journal ArticleDOI

Finding circles by an array of accumulators

TL;DR: This procedure is an extension and improvement of the circle-finding concept sketched by Duda and Hart as an extension of the Hough straight-line finder.