Ontology-Based Semantic Web Image Retrieval by Utilizing Textual and Visual Annotations

Authors:
Ja-Hwung Su;Bo-Wen Wang;Hsin-Ho Yeh;Vincent S. Tseng
Affiliations:
-;-;-;-
Venue:
WI-IAT '09 Proceedings of the 2009 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology - Volume 03
Year:
2009

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Abstract

The goal of traditional visual or textual-based image retrieval is to satisfy user’s queries by associating the images and semantic concepts effectively. As a result, perceptual structures of images have attracted researchers’ attention in recent studies. However, few past studies have been made on achieving semantic image retrieval by using image annotation techniques. To catch user’s ontological intention, we propose a new approach, namely Intelligent Web Image FetchER (iWIFER), which simultaneously considers the ontological requirements in usability, intelligence and effectiveness. Based on the proposed visual and textual-based annotation models, the image query becomes easy and effective. Through empirical evaluations, our annotation models can deliver accurate results for semantic web image retrieval.