Image retrieval algorithm based on Harris-Laplace corners and SVM relevance feedback

doi:10.1109/ICSESS.2016.7883080

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	Image retrieval algorithm based on Harris-Laplace corners and SVM relevance feedback
	Zhang, Yujiao
	2016-07-02
会议日期	August 26, 2016 - August 28, 2016
会议地点	Beijing, China
关键词	Content based retrieval Edge detection Laplace transforms Petroleum reservoir evaluation Software engineering Support vector machines Content based image retrieval Corner detector Evaluation index Harris-Laplace corners Image retrieval algorithms Relevance feedback Salient regions SVM classification
卷号	0
DOI	10.1109/ICSESS.2016.7883080
页码	337-340
英文摘要	The existing algorithms of content based image retrieval (CBIR) extract global features in the whole image to query, which have redundant calculation and will undoubtedly reduce the efficiency of the retrieval. In the light of this problem, an algorithm based on the combination of Harris-Laplace corners and support vector machine (SVM) relevance feedback is proposed in this paper. First, image corners are extracted by Harris-Laplace corner detector and the salient region is obtained by the density ratio in each distributed area of image corners. Then, color and shape in the salient region are fused for the initial retrieval. Finally, relevance feedback based on SVM classification is introduced into CBIR. The simulation results show that, the method proposed in this paper performs well in evaluation indexes of average precisions. © 2016 IEEE.
会议录	Proceedings of the IEEE International Conference on Software Engineering and Service Sciences, ICSESS
会议录出版者	IEEE Computer Society
语种	英语
ISSN号	23270586
内容类型	会议论文
源URL	[http://ir.lut.edu.cn/handle/2XXMBERH/117215]
专题	兰州理工大学
作者单位	School of Computer and Communication, Lanzhou University of Technology, Gansu; 730050, China
推荐引用方式 GB/T 7714	Zhang, Yujiao. Image retrieval algorithm based on Harris-Laplace corners and SVM relevance feedback[C]. 见:. Beijing, China. August 26, 2016 - August 28, 2016.