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Reseach Article

Efficient Keyword-Based Image Search on the Internet using Concept Ontology

Published on March 2012 by Dilipkumar A. Borikar
International Conference in Computational Intelligence
Foundation of Computer Science USA
ICCIA - Number 6
March 2012
Authors: Dilipkumar A. Borikar
97c824be-b9d9-425e-8be8-b3fe15126c76

Dilipkumar A. Borikar . Efficient Keyword-Based Image Search on the Internet using Concept Ontology. International Conference in Computational Intelligence. ICCIA, 6 (March 2012), 11-15.

@article{
author = { Dilipkumar A. Borikar },
title = { Efficient Keyword-Based Image Search on the Internet using Concept Ontology },
journal = { International Conference in Computational Intelligence },
issue_date = { March 2012 },
volume = { ICCIA },
number = { 6 },
month = { March },
year = { 2012 },
issn = 0975-8887,
pages = { 11-15 },
numpages = 5,
url = { /proceedings/iccia/number6/5131-1043/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 International Conference in Computational Intelligence
%A Dilipkumar A. Borikar
%T Efficient Keyword-Based Image Search on the Internet using Concept Ontology
%J International Conference in Computational Intelligence
%@ 0975-8887
%V ICCIA
%N 6
%P 11-15
%D 2012
%I International Journal of Computer Applications
Abstract

The tremendous growth of the World Wide Web has led to a considerable amount of information flooding in recent years. A huge volume of multimedia information that includes text, audio, video and image data, is being generated continuously, requiring the multimedia web databases to store them. This enormous data volume also necessitates efficient indexing mechanisms to facilitate faster retrieval. Multimedia systems and content-based image retrieval (CBIR) go hand in hand and they together have become one of the most challenging fields of research. CBIR addresses the problem of retrieval of relevant images from voluminous multimedia repositories using low-level image features. This work is aimed at retrieval of multimedia (specifically images) from the web. The CBIR approach is primarily an attribute-based representation of the images integrated with text-based retrieval. Web-pages containing the concept images are retrieved using the TF-IDF relationships. Concept ontology has been developed for augmenting the retrieval process. The proposed a keyword-based approach to image retrieval that uses the concept ontology information for intelligent retrieval eliminates manual annotation of images (web pages) by using ontology vocabulary in automated text extraction. Ontology serves as a means for providing semantic information about the objects in the domain of interest. Initial experimentation with the prototype system has lead to more precise search with a better average retrieval time. Use of concept ontology involving a document centered approach to image search yielded promising results.

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Index Terms

Computer Science
Information Sciences

Keywords

CBIR concept ontology semantic gap Image Content multimedia retrieval TF-IDF keyword-based image search