A review of hough transform and line segment detection approaches

In a wide range of image processing and computer vision problems, line segment detection is one of the most critical challenges. For more than three decades researchers have contributed to build more robust and accurate algorithms with faster performance. In this paper we review the main approaches and in particular the Hough transform and its extensions, which are among the most well-known techniques for the detection of straight lines in a digital image. This paper is based on extensive practical research and is organised into two main parts. In the first part, the HT and its major research directions and limitations are discussed. In the second part of the paper, state-of-the-art line segmentation techniques are reviewed and categorized into three main groups with fundamentally distinctive characteristics. Their relative advantages and disadvantages are compared and summarised in a table.

This published version of a conference paper is reproduced in this repository with permission from SCITEPRESS.
The paper is published by SCITEPRESS as: S. Rahmdel, P.; Comley, R.; Shi, D. and McElduff, S. (2015). A Review of Hough Transform and Line Segment Detection Approaches.In Proceedings of the 10th International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2015) ISBN 978-989-758-089-5, pages 411-418. DOI: 10.5220/0005268904110418.
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