DocumentCode
2127042
Title
A Relevance Feedback Image Retrieval Approach Based on RGA
Author
Liu, Quanzhong ; Wang, Jijun ; Feng, Guojie ; Zhang, Zifang
Author_Institution
Liaoning Key Lab. of Intell. Inf. Process., DaLian Univ., Dalian
fYear
2008
fDate
21-22 Dec. 2008
Firstpage
641
Lastpage
644
Abstract
Relevance Feedback is one of the key technologies of Content-Based Image Retrieval, which has an important impact on performance of retrieval. Give a Relevance Feedback image retrieval approach based on RGA. Introduce the relevant technologies and evaluation methods of Relevance Feedback. Expound the design of fitness function and genetic operator of real-code Genetic Algorithm. As show as the experiment, the methods improve the performance of retrieval, good results can be obtained.
Keywords
content-based retrieval; genetic algorithms; image retrieval; mathematical operators; relevance feedback; content-based image retrieval; fitness function; genetic operator; real-code genetic algorithm; relevance feedback image retrieval; Content based retrieval; Feedback; Genetic algorithms; Humans; Image databases; Image retrieval; Information retrieval; Knowledge acquisition; Laboratories; Radio frequency; genetic algorithm; image retrieval; real-code; relevance feedback;
fLanguage
English
Publisher
ieee
Conference_Titel
Knowledge Acquisition and Modeling, 2008. KAM '08. International Symposium on
Conference_Location
Wuhan
Print_ISBN
978-0-7695-3488-6
Type
conf
DOI
10.1109/KAM.2008.62
Filename
4732906
Link To Document