DocumentCode :
2726256
Title :
Proto-reduct Fusion Based Relevance Feedback in CBIR
Author :
Zutshi, Samar ; Wilson, Campbell ; Srinivasan, Bala
Author_Institution :
Swinburne Univ., VIC
fYear :
2009
fDate :
4-6 Feb. 2009
Firstpage :
121
Lastpage :
124
Abstract :
This paper proposes two related RF methods for use in CBIR. These two methods are based on a general classificatory analysis based framework for RF in CBMR that considers RF independently from retrieval. The proposed methods show how the user\´s information need expressed as a set of "proto-reducts\´\´ can be used as the basis of a re-weighting technique that can improve subsequent retrieval The performance of the proposed methods is studied on two image collections with different characteristics and compared against an existing RF method.
Keywords :
content-based retrieval; image fusion; image retrieval; relevance feedback; CBIR; content based image retrieval; proto-reduct fusion; re-weighting technique; relevance feedback; Feedback; CBIR; Relevance Feedback; Rough Sets;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Advances in Pattern Recognition, 2009. ICAPR '09. Seventh International Conference on
Conference_Location :
Kolkata
Print_ISBN :
978-1-4244-3335-3
Type :
conf
DOI :
10.1109/ICAPR.2009.46
Filename :
4782756
Link To Document :
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