Abstract
This paper proposes a new sequential similarity detection algorithm (SSDA), which can overcome matching error caused by grayscale distortion; meanwhile, time consumption is much less than that of regular algorithms based on image feature. The algorithm adopts Sobel operator to deal with subgraph and template image, and regards the region which has maximum relevance as final result. In order to solve time-consuming problem existing in original algorithm, a coarse-to-fine matching method is put forward. Besides, the location correlation keeps updating and remains the minimum value in the whole scanning process, which can significantly decrease time consumption. Experiments show that the algorithm proposed in this article can not only overcome gray distortion, but also ensure accuracy. Time consumption is at least one time orders of magnitude shorter than that of primal algorithm.
Article PDF
Similar content being viewed by others
Explore related subjects
Discover the latest articles, news and stories from top researchers in related subjects.Avoid common mistakes on your manuscript.
References
Ma G H, Wang L, Liu Q Q, et al. Research on image process and tracing of a welding robot [J]. Lecture Notes in Electrical Engineering, 2010, 88: 253–259.
Chen Xi-zhang, Chen Shan-ben. Recognition and positioning of start welding position for arc welding robot [J]. Transactions of the China Welding Institution, 2009, 30(4): 18–20 (in Chinese).
Chen X Z, Chen S B, Lin T, et al. Practical method to locate the initial weld position usingvisual technology [J]. International Journal of Advanced Manufacturing Technology, 2006, 30: 663–668.
Zhu Zhen-you, Piao Yong-jie, Lin Tao, et al. Visualbased research on weld seam initial position recognition in local environment [J]. Transactions of the China Welding Institution, 2004, 25(2): 95–98 (in Chinese).
Liu Guo-ping, Wang Hong-liang, Hu Rong-hua, et al. Application of template matching in welding image [J]. Welding Technology, 2004, 33(4): 14–15 (in Chinese).
Zhu Yong-song, Guo Cheng-ming. The research of correlation matching algorithm based on correlation coefficient [J]. Signal Processing, 2003, 19(6): 531–534 (in Chinese).
Brown L G. A survey of image registration techniques [J]. ACM Computing Surveys, 1992, 24: 325–376.
Bernea D I, Silverman H F. A class of algorithms for fast digital registration [J]. IEEE Transactions on Computers, 1972, 21(2): 179–186
Mi Chang-wei, Liu Xiao-li, Xu Ming-you. An advanced algorithm based on SSDA [J]. Journal of Projectiles, Rockets, Missiles and Guidance, 2004, 24(1): 85–87 (in Chinese).
Li Jun-shan, Tan Yuan-yuan, Zhang Yuan-li. An improved SSDA [J]. Electronics Optics & Control, 2007, 14(2): 66–68 (in Chinese).
Luo Zhong-xuan, Liu Cheng-ming. Fast algorithm of image matching [J]. Journal of Computer-Aided Design & Computer Graphics, 2005, 17(5): 966–970 (in Chinese).
Tian Ying, Yuan Wei-qi. Application of the genetic algorithm in image processing [J]. Journal of Image and Graphics, 2007, 12(3): 389–396 (in Chinese).
Xiong Guo-qing, Yu Qi-feng. Fast matching algorithm for real-time tracking [J]. Journal of Computer-Aided Design & Computer Graphics, 2002, 14(1): 41–43 (in Chinese).
Yan Bo-jun, Zheng Lian, Wang Ke-yong. Fast targetdetecting algorithm based on invariant moment [J]. Infrared Technology, 2001, 23(6): 8–12 (in Chinese).
Wu Pei-jing, Chen Guang-meng. An improved SSDA in image registration [J]. Computer Engineering and Applications, 2005, 33: 76–78 (in Chinese).
Chen Wei-bing, Shu Hui. Research on fast edge matching algorithm [J]. Computer Engineering and Design, 2004, 25(1): 130–132(in Chinese).
Author information
Authors and Affiliations
Corresponding author
Additional information
Foundation item: the National Natural Science Foundation of China (No. 61165008)
Rights and permissions
About this article
Cite this article
Ma, Gh., Wang, C., Liu, P. et al. Sequential similarity detection algorithm based on image edge feature. J. Shanghai Jiaotong Univ. (Sci.) 19, 79–83 (2014). https://doi.org/10.1007/s12204-013-1465-3
Received:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s12204-013-1465-3