Improved Hough transform for curve detection based on directional control of connected regions
Yu Shi, Jie Yuan, Guoyou Wang, Xiuhua Li · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2012
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.