Image Distance Measure Based on Adaptive Patch Matching

被引：0
|
作者：
Yu, Yan [1 ,2 ]
Wang, Tianjiang [1 ]
Chen, Ying [3 ]
Li, Jinsheng [3 ]
Liu, Tan [3 ]
机构：
[1] Huazhong Univ Sci & Technol, Sch Comp Sci & Technol, Wuhan, Peoples R China
[2] Wuhan Univ Sci & Technol, Sch Sci, Wuhan, Peoples R China
[3] Wuhan Intelligent Engn Co Ltd, CSCEC, Wuhan, Peoples R China
来源：
2014 SEVENTH INTERNATIONAL SYMPOSIUM ON COMPUTATIONAL INTELLIGENCE AND DESIGN (ISCID 2014), VOL 2 | 2014年
关键词：
image distance measure; image retrieval; image patch; Hungarian algorithm; local binary pattern; CLASSIFICATION;
D O I：
10.1109/ISCID.2014.191
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This paper presents a novel approach to measuring distance between images and exploit it for image retrieval. Firstly, each image is presented as a set of patches, integrating both the local appearance feature and spatial information of patches. Secondly, the set of matching costs between all pairs of patches of two images is computed. Then the distance between two images is obtained by minimize the total cost of matching using Hungarian algorithm. Finally, we test our image distance measure method in colorful image retrieval. The experimental results indicate that the proposed method outperforms other existing image distance measure methods.
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页数：4
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