Sequential Similarity Detection Algorithm Based on Image Edge Feature

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 su...

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Bibliographic Details
Published in:Shanghai jiao tong da xue xue bao 2014-02, Vol.19 (1), p.79-83
Main Author: 马国红 王聪 刘沛 朱书林
Format: Article
Language:English
Subjects:
Algorithms
Architecture
Computer Science
Correlation
Distortion
Electrical Engineering
Engineering
Error detection
Image detection
Life Sciences
Matching
Materials Science
Scanning
Similarity
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Summary: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.
ISSN:1007-1172
1995-8188
DOI:10.1007/s12204-013-1465-3