Semantic-based image retrieval: A fuzzy modeling approach

Author

Lakdashti, Abolfazl ; Moin, M. Shahram ; Badie, Kambiz

Author_Institution

Islamic Azad Univ., Sari

fYear

2008

fDate

March 31 2008-April 4 2008

Firstpage

575

Lastpage

581

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;

fLanguage

English

Publisher

ieee

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

Type

conf

DOI

10.1109/AICCSA.2008.4493589

Filename

4493589