DocumentCode :
538090
Title :
Image retrieval based on color, texture, shape and SVM relevance feedback
Author :
Yu, Xia ; Huang, XiaoSha
Author_Institution :
Coll. of Inf. Sci. & Eng., Shenyang Univ. of Technol., Shenyang, China
Volume :
1
fYear :
2010
fDate :
17-19 Nov. 2010
Firstpage :
779
Lastpage :
781
Abstract :
After the research of the principle of SVM, it is applied to the relevance feedback of the content-based image retrieval. First do a initial retrieval separately by MEPG-7 Dominating Color, Gray-level Co-occurrence Matrix and histogram, then do a feedback using the SVM for the new round retrieval. In the experiment we comparing the SVM feedback result with the result of weight adjusting-based algorithm, prove that SVM feedback can greatly improve the recall level, get more items that be of interest to the user.
Keywords :
content-based retrieval; image colour analysis; image retrieval; image texture; relevance feedback; support vector machines; video coding; MEPG-7 dominating color; SVM relevance feedback; content-based image retrieval; gray-level co-occurrence matrix; support vector machine; weight adjusting-based algorithm; Histograms; Multimedia communication; Support vector machines; SVM; Weights adjusting; content-based image retrieval; relevance feedback;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer-Aided Industrial Design & Conceptual Design (CAIDCD), 2010 IEEE 11th International Conference on
Conference_Location :
Yiwu
Print_ISBN :
978-1-4244-7973-3
Type :
conf
DOI :
10.1109/CAIDCD.2010.5681233
Filename :
5681233
Link To Document :
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