Paper
19 November 2012 Improved Hough transform for curve detection based on directional control of connected regions
Yu Shi, Jie Yuan, Guoyou Wang, XiuHua Li
Author Affiliations +
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.
© (2012) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Yu Shi, Jie Yuan, Guoyou Wang, and XiuHua Li "Improved Hough transform for curve detection based on directional control of connected regions", Proc. SPIE 8542, Electro-Optical Remote Sensing, Photonic Technologies, and Applications VI, 85420Y (19 November 2012); https://doi.org/10.1117/12.936028
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KEYWORDS
Hough transforms

Detection and tracking algorithms

Sensors

Binary data

Computer vision technology

Machine vision

Computer simulations

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