Title :
Semantic-based image retrieval: A fuzzy modeling approach
Author :
Lakdashti, Abolfazl ; Moin, M. Shahram ; Badie, Kambiz
Author_Institution :
Islamic Azad Univ., Sari
fDate :
March 31 2008-April 4 2008
Abstract :
In this paper, we propose a new fuzzy based image retrieval approach to reduce the semantic gap in content-based image retrieval systems. Our main contributions are: (1) an algorithm for reduction of feature space dimensionality, (2) a fuzzy modeling approach to model the expert human behavior in the image retrieval task, (3) a fuzzy system for semantic-based image retrieval, and (4) a training algorithm for creating the fuzzy rules. The proposed solution not only is a novel idea in the semantic-based image retrieval field, but also has enough potential in learning semantics from users and making a powerful approach to improve the performance of CBIR systems, as the results of our experiments on a set of 2000 images support our claim.
Keywords :
content-based retrieval; fuzzy set theory; image retrieval; semantic networks; content-based image retrieval systems; expert human behavior; feature space dimensionality reduction; fuzzy modeling approach; learning semantics; semantic gap reduction; semantic-based image retrieval; training algorithm; Availability; Content based retrieval; Digital cameras; Digital images; Fuzzy systems; Humans; Image retrieval; Information retrieval; Internet; Shape measurement;
Conference_Titel :
Computer Systems and Applications, 2008. AICCSA 2008. IEEE/ACS International Conference on
Conference_Location :
Doha
Print_ISBN :
978-1-4244-1967-8
Electronic_ISBN :
978-1-4244-1968-5
DOI :
10.1109/AICCSA.2008.4493589
