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http://dx.doi.org/10.3745/KIPSTB.2004.11B.4.509

Semantic Image Retrieval Using Color Distribution and Similarity Measurement in WordNet  

Choi, Jun-Ho (조선대학교 대학원 전자계산학과)
Cho, Mi-Young (조선대학교 대학원 전자계산학과)
Kim, Pan-Koo (조선대학교 컴퓨터공학부)
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 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 propose a method for computerized semantic similarity calculation In WordNet space. We consider the edge, depth, link type and density as well as existence of common ancestors. Also, we have introduced method that applied similarity measurement on semantic image retrieval. To combine wi#h the low level features, we use the spatial color distribution model. When tested on a image set of Microsoft's 'Design Gallery Line', proposed method outperforms other approach.
Keywords
Image Retrieval; WordNet; Similarity Measurement; Color Distribution;
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