Hershey, Pennsylvania
New York, New YorkBeijing, China
A User-Driven Ontology Guided Image Retrieval Model

A User-Driven Ontology Guided Image Retrieval Model

Lisa Fan (University of Regina, Canada) and Botang Li (University of Regina, Canada)
Copyright: © 2009 |Pages: 12
DOI: 10.4018/jcini.2009070106
OnDemand:
(Individual Articles)
Available
$37.50
Current Special Offers
No Current Special Offers
TOTAL SAVINGS: $37.50

Abstract

The demand for image retrieval and browsing online is growing dramatically. There are hundreds of millions of images available on the current World Wide Web. For multimedia documents, the typical keyword-based retrieval methods assume that the user has a specific goal in mind by using accurate query keywords in searching a set of images. Whereas the users may face with a repository of images whose domain is less known and content is semantically complicated, or the users may only generally know what they search for. In these cases it is difficult to decide what exact keywords to use for the query. In this article, we propose a user-centered image retrieval method that is based on the current Web, keyword-based annotation structure, and combining Ontology guided knowledge representation and probabilistic ranking. A prototype of web application for image retrieval using the proposed approach has been implemented. The model provides a recommendation subsystem to support and assist the user modifying the queries and reduces the user’s cognitive load with the searching space. Experimental results show that the image retrieval recall and precision rates increased and therefore demonstrates the effectiveness of the model.

Complete Article List

Search this Journal:
Reset
Volume 19: 1 Issue (2025)
Volume 18: 1 Issue (2024)
Volume 17: 1 Issue (2023)
Volume 16: 1 Issue (2022)
Volume 15: 4 Issues (2021)
Volume 14: 4 Issues (2020)
Volume 13: 4 Issues (2019)
Volume 12: 4 Issues (2018)
Volume 11: 4 Issues (2017)
Volume 10: 4 Issues (2016)
Volume 9: 4 Issues (2015)
Volume 8: 4 Issues (2014)
Volume 7: 4 Issues (2013)
Volume 6: 4 Issues (2012)
Volume 5: 4 Issues (2011)
Volume 4: 4 Issues (2010)
Volume 3: 4 Issues (2009)
Volume 2: 4 Issues (2008)
Volume 1: 4 Issues (2007)
View Complete Journal Contents Listing