DocumentCode :
2152435
Title :
Different relevance feedback techniques in CBIR: A survey and comparative study
Author :
Sivakamasundari, G. ; Seenivasagam, V.
Author_Institution :
Dept. of CSE, Nat. Eng. Coll., Kovilpatti, India
fYear :
2012
fDate :
21-22 March 2012
Firstpage :
1115
Lastpage :
1121
Abstract :
In Content Based Image Retrieval (CBIR), there is semantic gap between the low level features and high level concepts. Advent of different relevance feedback techniques bridges the gap. Different techniques use different assumption. Yet there are some performance metrics which quantitatively measure and compare different relevance feedback algorithms. This is necessary to make the CBIR system work consistently. In this paper we analyze different relevance feedback algorithm starting from conventional to recent technique.
Keywords :
content-based retrieval; image retrieval; relevance feedback; CBIR system; content based image retrieval; high level concepts; low level features; performance metrics; relevance feedback techniques; Atmospheric measurements; Lead; Navigation; Particle measurements; Visualization; Navigation pattern relevance feedback; Particle Swarm Optimization; Query modification; Query re-weighting; log based relevance feedback;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computing, Electronics and Electrical Technologies (ICCEET), 2012 International Conference on
Conference_Location :
Kumaracoil
Print_ISBN :
978-1-4673-0211-1
Type :
conf
DOI :
10.1109/ICCEET.2012.6203830
Filename :
6203830
Link To Document :
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