Fast randomized algorithm for center-detection

Authors:
Kuo-Liang Chung;Yong-Huai Huang;Jyun-Pin Wang;Ting-Chin Chang;Hong-Yuan Mark Liao
Affiliations:
Department of Computer Science and Information Engineering, National Taiwan University of Science and Technology, No. 43, , Keelung Road, Taipei, Taiwan 10672, Republic of China;Institute of Computer and Communication Engineering and Department of Electronic Engineering, Jinwen University of Science and Technology, No. 99, An-Chung Road, Hsin-Tien, Taipei 23154, Taiwan, R ...;Department of Computer Science and Information Engineering, National Taiwan University of Science and Technology, No. 43, , Keelung Road, Taipei, Taiwan 10672, Republic of China;Department of Computer Science and Information Engineering, National Taiwan University of Science and Technology, No. 43, , Keelung Road, Taipei, Taiwan 10672, Republic of China;Institute of Information Science, Academia Sinica, No. 128, Academia Road, , Taipei, Taiwan 115, Republic of China
Venue:
Pattern Recognition
Year:
2010

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Abstract

Recently, Cauchie et al. presented an adaptive Hough transform-based algorithm to successfully solve the center-detection problem which is an important issue in many real-world problems. This paper presents a fast randomized algorithm to solve the same problem. With similar memory requirement and accuracy, the computational complexity analysis and comparison show that our proposed algorithm performs much better in terms of efficiency. We have tested our algorithm on 13 real images. Experimental results indicated that our algorithm has 38% execution-time improvement over Cauchie et al.'s algorithm. The extension of the proposed algorithm to detect multiple centers is also addressed.