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A new fast and robust template matching with randomness

  • Beijing Institute of Technology

科研成果: 书/报告/会议事项章节会议稿件同行评审

摘要

Template matching is one of the most important techniques in computer vision, where the algorithm should find the location of template image in scene image. The commonly used method of template matching is Normalized Cross Correlation which has a high matching accuracy while consuming a large amount of computational speed. In this paper, a novel, fast and robust template matching approach is proposed. The new algorithm randomly visits the pixels and locates local maxima by gradually moving to the regions with larger NCC values. To further improve the speed and accuracy of the algorithm, several additional rules are established. Theoretical analysis and experimental results show that the proposed algorithm maintain a high matching accuracy while providing a significant speedup.

源语言英语
主期刊名Proceedings of the 29th Chinese Control and Decision Conference, CCDC 2017
出版商Institute of Electrical and Electronics Engineers Inc.
1053-1058
页数6
ISBN(电子版)9781509046560
DOI
出版状态已出版 - 12 7月 2017
活动29th Chinese Control and Decision Conference, CCDC 2017 - Chongqing, 中国
期限: 28 5月 201730 5月 2017

出版系列

姓名Proceedings of the 29th Chinese Control and Decision Conference, CCDC 2017

会议

会议29th Chinese Control and Decision Conference, CCDC 2017
国家/地区中国
Chongqing
时期28/05/1730/05/17

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