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