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Sequential Similarity Detection Algorithm Based on Image Edge Feature 被引量:4
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作者 马国红 王聪 +1 位作者 刘沛 朱书林 《Journal of Shanghai Jiaotong university(Science)》 EI 2014年第1期79-83,共5页
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 bas... 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. 展开更多
关键词 welding image feature matching sequential similarity detection algorithm(SSDA) self-adaption value
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