CVFeb 7, 2015

A Survey on Hough Transform, Theory, Techniques and Applications

arXiv:1502.02160v1144 citations
Originality Synthesis-oriented
AI Analysis

It provides a comprehensive overview for researchers and practitioners in computer vision, but is incremental as it synthesizes existing knowledge without new results.

This paper surveys the Hough transform, detailing its theory, variations like line and circle transforms, and applications, while addressing challenges such as high storage and computation demands.

For more than half a century, the Hough transform is ever-expanding for new frontiers. Thousands of research papers and numerous applications have evolved over the decades. Carrying out an all-inclusive survey is hardly possible and enormously space-demanding. What we care about here is emphasizing some of the most crucial milestones of the transform. We describe its variations elaborating on the basic ones such as the line and circle Hough transforms. The high demand for storage and computation time is clarified with different solution approaches. Since most uses of the transform take place on binary images, we have been concerned with the work done directly on gray or color images. The myriad applications of the standard transform and its variations have been classified highlighting the up-to-date and the unconventional ones. Due to its merits such as noise-immunity and expandability, the transform has an excellent history, and a bright future as well.

Foundations

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