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.
MA Guo-hong* (马国红), WANG Cong (王 聪), LIU Pei (刘 沛), ZHU Shu-lin (朱书林)
. Sequential Similarity Detection Algorithm Based on Image Edge Feature[J]. Journal of Shanghai Jiaotong University(Science), 2014
, 19(1)
: 79
-83
.
DOI: 10.1007/s12204-013-1465-3
[1] 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.
[2] 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).
[3] 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.
[4] 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).
[5] 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).
[6] 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).
[7] Brown L G. A survey of image registration techniques[J]. ACM Computing Surveys, 1992, 24: 325-376.
[8] Bernea D I, Silverman H F. A class of algorithms for fast digital registration [J]. IEEE Transactions on Computers, 1972, 21(2): 179-186
[9] 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).
[10] Li Jun-shan, Tan Yuan-yuan, Zhang Yuan-li. An improved SSDA [J]. Electronics Optics & Control, 2007,14(2): 66-68 (in Chinese).
[11] 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).
[12] 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).
[13] 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).
[14] 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).
[15] Wu Pei-jing, Chen Guang-meng. An improved SSDA in image registration [J]. Computer Engineering and Applications, 2005, 33: 76-78 (in Chinese).
[16] Chen Wei-bing, Shu Hui. Research on fast edge matching algorithm [J]. Computer Engineering and Design, 2004, 25(1): 130-132(in Chinese).
