Robust template matching algorithm with multi-feature using best-buddies similarity
文献类型：会议论文
| 作者 | Jiang SP(江苏蓬)1,2,3,4,5 ; Xiang W(向伟)1,3,4,5; Liu YP(刘云鹏)1,3,4,5
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| 出版日期 | 2019 |
| 会议日期 | August 28-30, 2019 |
| 会议地点 | Shenyang, China |
| 关键词 | Template Matching Best-Buddies Similarity HOG Feature Confidence Map |
| 页码 | 1-6 |
| 英文摘要 | In order to solve the problem of matching failure of BBS (Best-Buddies Similarity) algorithm when the target image has a partial occlusion, cluttered background, imbalance illumination, and nonrigid deformation. A multi-feature template matching algorithm based on the BBS algorithm is proposed in this paper. On the basis of the location features and appearance features, we add HOG (Histogram of Oriented Gradients) features to make full use of the color, position and structural contour of the target image to match. In addition, we also perform mean filtering on the confidence map. The experimental results show that the AUC (Area Under Curve) score of the proposed algorithm is 0.6119, which is 6.38% higher than the BBS algorithm. Moreover, our algorithm has stronger robustness and higher matching accuracy. |
| 源文献作者 | Chinese Society for Optical Engineering |
| 产权排序 | 1 |
| 会议录 | Second Target Recognition and Artificial Intelligence Summit Forum
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| 会议录出版者 | SPIE |
| 会议录出版地 | Bellingham, USA |
| 语种 | 英语 |
| ISSN号 | 0277-786X |
| ISBN号 | 978-1-5106-3631-6 |
| WOS记录号 | WOS:000546230500067 |
| 源URL | [http://ir.sia.cn/handle/173321/26417]  |
| 专题 | 沈阳自动化研究所_光电信息技术研究室 |
| 通讯作者 | Jiang SP(江苏蓬) |
| 作者单位 | 1.Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, China 2.University of Chinese Academy of Sciences, Beijing, China 3.Key Laboratory of Opto-Electronic Information Processing, CAS, Shenyang, China 4.Key Lab of Image Understanding and Computer Vision, Shenyang, China 5.Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang, China |
| 推荐引用方式 GB/T 7714 | Jiang SP,Xiang W,Liu YP. Robust template matching algorithm with multi-feature using best-buddies similarity[C]. 见:. Shenyang, China. August 28-30, 2019. |
入库方式： OAI收割
来源：沈阳自动化研究所
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