Sequential Similarity Detection Algorithm Based on Image Edge Feature

doi:10.1007/s12204-013-1465-3

上海交通大学学报（英文版） ›› 2014, Vol. 19 ›› Issue (1): 79-83.doi: 10.1007/s12204-013-1465-3

Sequential Similarity Detection Algorithm Based on Image Edge Feature

MA Guo-hong* (马国红), WANG Cong (王聪), LIU Pei (刘沛), ZHU Shu-lin (朱书林)

(School of Mechanical & Electrial Engineering, Nanchang University, Nanchang 330031, China)

出版日期:2014-01-15 发布日期:2014-01-15
通讯作者: MA Guo-hong (马国红) E-mail: ghma2006@gmail.com

Sequential Similarity Detection Algorithm Based on Image Edge Feature

MA Guo-hong* (马国红), WANG Cong (王聪), LIU Pei (刘沛), ZHU Shu-lin (朱书林)

(School of Mechanical & Electrial Engineering, Nanchang University, Nanchang 330031, China)

Online:2014-01-15 Published:2014-01-15
Contact: MA Guo-hong (马国红) E-mail: ghma2006@gmail.com

摘要/Abstract

摘要： 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.

关键词: welding image, feature matching, sequential similarity detection algorithm (SSDA), self-adaption value

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.

Key words: welding image, feature matching, sequential similarity detection algorithm (SSDA), self-adaption value

中图分类号:

TG 409

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]. 上海交通大学学报（英文版）, 2014, 19(1): 79-83.

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.

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Sequential Similarity Detection Algorithm Based on Image Edge Feature

Sequential Similarity Detection Algorithm Based on Image Edge Feature

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