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Proceedings Paper

Improved Hough transform for curve detection based on directional control of connected regions
Author(s): Yu Shi; Jie Yuan; Guoyou Wang; XiuHua Li
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Paper Abstract

Accurate and fast curve detection in images is a challenging computer vision problem. HT(Hough transform) is one of the most widely used techniques for curve detection. Existing HT-based methods have disadvantages of low accuracy and low speed. In this paper, a new and efficient Hough Transform for curve detection is presented. In view of kinematics, a curve can be regarded as movement trajectory of a given point, and point's velocity direction is the tangential direction of point on the smooth curve. Thus the main contributions are threefold. 1) We formulate the problem of curve detection as robustly fit curve in the connected region. 2) We propose the direction elements and directional control scheme to quickly discover the smooth curve. 3) We use a coarse-to-fine strategy to efficiently detect the final curve. We have tested our algorithm on simulated and natural image. Compared to other classical curve detection methods, experimental results indicated that our algorithm reduces the time cost and improves the detection accuracy greatly.

Paper Details

Date Published: 19 November 2012
PDF: 10 pages
Proc. SPIE 8542, Electro-Optical Remote Sensing, Photonic Technologies, and Applications VI, 85420Y (19 November 2012); doi: 10.1117/12.936028
Show Author Affiliations
Yu Shi, Huazhong Univ. of Science and Technology (China)
Jie Yuan, Huazhong Univ. of Science and Technology (China)
Guoyou Wang, Huazhong Univ. of Science and Technology (China)
XiuHua Li, Huazhong Univ. of Science and Technology (China)


Published in SPIE Proceedings Vol. 8542:
Electro-Optical Remote Sensing, Photonic Technologies, and Applications VI
Gary W. Kamerman; Gary J. Bishop; Mark T. Gruneisen; Keith L. Lewis; Miloslav Dusek; Richard C. Hollins; Ove Steinvall; John Gonglewski; John G. Rarity; Thomas J. Merlet, Editor(s)

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