Concept-based image retrieval using the new semantic similarity measurement

Authors:
Junho Choi;Miyoung Cho;Se Hyun Park;Pankoo Kim
Affiliations:
Dept. of Computer Science and Engineering, Chosun University, Gwangju, Korea;Dept. of Computer Science and Engineering, Chosun University, Gwangju, Korea;Dept. of Computer Science and Engineering, Chosun University, Gwangju, Korea;Dept. of Computer Science and Engineering, Chosun University, Gwangju, Korea
Venue:
ICCSA'03 Proceedings of the 2003 international conference on Computational science and its applications: PartI
Year:
2003

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Abstract

Semantic interpretation of image is incomplete without some mechanism for understanding semantic content that is not directly visible. For this reason, human assisted content-annotation through natural language is an attachment of textual description (i.e. a keyword, or a simple sentence) to image. However, keyword-based retrieval is in the level of syntactic pattern matching. In other words, dissimilarity computation among terms is usually done by using string matching not concept matching. In this paper, we present a solution for qualitative measurement of concept-based retrieval of annotated image. We propose a method for computerized conceptual similarity distance calculation in WordNet space. Also we have introduced method that applied similarity measurement on concept-based image retrieval. When tested on a image set of Microsoft's 'Design Gallery Live', proposed method outperforms other approach.