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 at-tachment 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.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
George A. Miller “Introduction to WordNet: An On-line Lexical Database”, International Journal of Lexicography, 1990.
Sussna “WordSense Disambiguation for Free-text Indexing Using a Massive Semantic Net-work” Proceedings of the Second International Conference on Information and Knowledge Management, CIKM’93.
Philip Resnik “Using Information Content to Evaluate Semantic Similarity in a Taxonomy” Proceedings of the 14th International Joint Conference on Artificial Intelligence, 1995.
R. Richardson, A.F. Smeaton “Using WordNet in a Knowledge-Based Approach to Information Retrieval”, Working paper, CA-0395, School of Computer Applications, Dublin City University, Ireland, 1995
Eneko Agirre and German Rigau, “Word sense disambiguation using conceptual density”. In Proceedings of the 16th International Conference on Computational Linguistics, pp. 16–22, Copenhagen, 1996.
Jay J Jiang, David W. Conrath “Semantic Similarity Based Corpus Statistics and Lexical Taxonomy”, Proc. Of International Conference Research on Computational Linguistics, 1997.
Y. Alp Aslandogan, et.al. “Using Semantic contents and WordNet in image retrieval”, Proceeding of ACM SIGIR 97, pp 286–295, Philadelphia PA, USA.
J. Z. Wang, J. Li, D. Chan, G. Wiederhold, “Semantics-sensitive Retrieval or Digital Picture Libraries” D-Lib. Magazine, 1999.
Y.C. Park, F. Golshani, S. Panchanathan, “Conceptualization and Ontology: Tools for Effi-cient Storage and Retrieval of Semantic Visual Information”, Internet Multimedia Management Systems Conference, 2000.
Y.C. Park, P.K. Kim, F. Golshani, S. Panchanathan “Concept-based visual information management with large lexical corpus” DEXA, 2001.
Kobus Barnard, Pinar Duygulu, David Forsyth “Clustering Art” In IEEE conf. on Computer vision and Pattern Recognition, 2001.
K Barnard, D.A. Forsyth. “Learning the semantics of words and pictures. In int. Conf. on Computer Vision, 2001.
Guarino, N. and Welty, C. “Supporting Ontological Analysis of Taxonomic Relationships”. Data and Knowledge Engineering (in press), 2001.
Budanitsky, A., and G. Hirst, “Semantic Distance in WordNet: An Experimental, Applica-tion-oriented Evaluation of Five Measures”, Workshop on WordNet and Other Lexical Re-sources, in the North American Chapter of the Association for Computational Linguistics (NAACL-2000), Pittsburgh, PA, June 2001.
K Barnard, P Duygulg, J.F.G. de Freitas, D.A. Forsyth “Object Recognition as Machine Translation: Learning a Lexicon for a Fixed Image vocabulary”, Seventh European Conference on Computer Vision, 2002.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2003 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Choi, J., Cho, M., Park, S.H., Kim, P. (2003). Concept-Based Image Retrieval Using the New Semantic Similarity Measurement. In: Kumar, V., Gavrilova, M.L., Tan, C.J.K., L’Ecuyer, P. (eds) Computational Science and Its Applications — ICCSA 2003. ICCSA 2003. Lecture Notes in Computer Science, vol 2667. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44839-X_9
Download citation
DOI: https://doi.org/10.1007/3-540-44839-X_9
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-40155-1
Online ISBN: 978-3-540-44839-6
eBook Packages: Springer Book Archive