DocumentCode :
1683495
Title :
A recursive optimal relevance feedback scheme for content based image retrieval
Author :
Doulamis, Nikolaos ; Doulamis, Anastasios
Author_Institution :
Dept. of Electr. & Comput. Eng., Nat. Tech. Univ. of Athens, Greece
Volume :
2
fYear :
2001
Firstpage :
741
Abstract :
An optimal relevance algorithm is proposed, which adapts the response of a content based image retrieval (CBIR) system to the user\´s information needs. In particular, the importance of each descriptor to the similarity measure of the system is estimated so that the correlation between the query image and all images marked by the user as relevant is maximized while simultaneously the correlation over all irrelevant images is minimized. Other degree of relevance can be also included in the proposed scheme. In case the user applies more than one feedback iteration, a recursive algorithm is introduced for increasing the system efficiency. Convergence of the proposed scheme is achieved if "consistent" relevant and irrelevant images are selected by the user
Keywords :
content-based retrieval; correlation methods; image processing; image retrieval; iterative methods; relevance feedback; content-based retrieval; feedback iteration; image retrieval; irrelevant images; recursive algorithm; recursive optimal relevance feedback scheme; relevant images; similarity measure; Computational complexity; Content based retrieval; Convergence; Face; Feedback; Humans; Image retrieval; Information retrieval; Information systems; Particle measurements;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image Processing, 2001. Proceedings. 2001 International Conference on
Conference_Location :
Thessaloniki
Print_ISBN :
0-7803-6725-1
Type :
conf
DOI :
10.1109/ICIP.2001.958600
Filename :
958600
Link To Document :
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