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Semantic Image Retrieval Based on Ontology and SPARQL Query

Published on August 2011 by N. Magesh, Dr. P. Thangaraj
journal_cover_thumbnail

International Conference on Advanced Computer Technology
Foundation of Computer Science USA
ICACT - Number 1
August 2011
Authors: N. Magesh, Dr. P. Thangaraj
cde3e0cc-d5ec-4893-ab69-d254e7acf457

N. Magesh, Dr. P. Thangaraj . Semantic Image Retrieval Based on Ontology and SPARQL Query. International Conference on Advanced Computer Technology. ICACT, 1 (August 2011), 12-16.

@article{
author = { N. Magesh, Dr. P. Thangaraj },
title = { Semantic Image Retrieval Based on Ontology and SPARQL Query },
journal = { International Conference on Advanced Computer Technology },
issue_date = { August 2011 },
volume = { ICACT },
number = { 1 },
month = { August },
year = { 2011 },
issn = 0975-8887,
pages = { 12-16 },
numpages = 5,
url = { /proceedings/icact/number1/3229-icact070/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 International Conference on Advanced Computer Technology
%A N. Magesh
%A Dr. P. Thangaraj
%T Semantic Image Retrieval Based on Ontology and SPARQL Query
%J International Conference on Advanced Computer Technology
%@ 0975-8887
%V ICACT
%N 1
%P 12-16
%D 2011
%I International Journal of Computer Applications
Abstract

The main objective of this paper is how to use the ontology for semantic image annotation and search in huge collection of images. We have presentenced a framework for applying the semantics to enhance image retrieval. The entire problem is considered in two levels. First, An ontology is created to define the semantic space. Secondly, Natural language sentences are converted in to SPARQL statements and the relevant images are accessed using SPARQL query. The ontologies are represented in RDF form and these are based on existing data standard and knowledge corpura. Since the RDF structure provides the formal way of annotating the images, the image retrieval task is simplified as compared with earlier approaches. Retrieval is done by using the keyword (thesauri) description. We also show that we are able to retrieve desired images using the SPARQL query language (7).

References
  1. N.Magesh - “ Machine Translator “, National Conference on Soft Computing held in 19-20 March 2009 at IRTT, Erode.
  2. N.Magesh - “ Knowledge Based Approach for Language translation “ Organized by Computer Science and Engineering at Vellalar College of Engg and Technology Erode02. National Conference on Recent Trents in Innovative Technologies on Novenber 2009.
  3. Eugenio Di Sciascio, Francesco M.Donini, Marina “ Structured Knowledge Representation for Image Retrieval ” BARI Italy.
  4. EeroHyv, SamppaSaarela, Kim Viljanen -“Ontology-Based Image Retrieval” by. Department of Computer Science, P.O. Box 26
  5. Website:http://www.w3.org.- "Resource Description Framework (RDF)”
  6. Van Rijsbergen, "Information Retrieval", London: Butterworths, Second Edition. Website : www.w3.org/rdf-sparql-query “SPARQL Query Language for RDF”
  7. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, VOL. 29, NO. 3, MARCH 2007, Gustavo Carneiro, Antoni B. Chan, Pedro J. Moreno, and NunoVasconcelosSupervised Learning of Semantic Classes for Image annotation and Retrieval.
  8. Elsevier, Image and Vision Computing 22 (2004) 251–267, “Language-based querying of image collections on the basis of an extensible ontology”, Christopher Town, David Sinclair,
  9. Myunggwon Hwang, Hyunjang Kong, Pankoo Kim - “The Design of the Ontology Retrieval System on the Web”, ICA0T2006, Feb. 2006.
Index Terms

Computer Science
Information Sciences

Keywords

Information retrieval Semantic Web Image retrieval Ontology Thesaurus RDF and OWL