Matching colors with KANSEI vocabulary using similarity measure based on wordnet

Authors:
Sunkyoung Baek;Miyoung Cho;Pankoo Kim
Affiliations:
Dept. of Computer Science, Chosun University, Gwangju, Korea;Dept. of Computer Science, Chosun University, Gwangju, Korea;Dept. of CSE, Chosun University, Korea
Venue:
ICCSA'05 Proceedings of the 2005 international conference on Computational Science and its Applications - Volume Part I
Year:
2005

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Abstract

Recently, the image retrieval based on content is capable of understanding the semantics of visual information. However, it is hard to represent emotion or feeling of human. To approach more intelligent content-based retrieval, we focus on KANSEI information. This paper presents a method of matching color, which is part of visual information associated with KANSEI-vocabulary relation. We use WordNet that is a kind of lexical ontology by relations between words. We define relation for matching between color and KANSEI vocabulary using the meaning of color table. We propose the similarity measure between Color-KANSEI vocabulary and query. After experiment we can find the best pertinent color using Lesk algorithm. The significance of our study is finding semantically pertinent color according to various queries based on WordNet. This is the approach as computing vocabulary to show KANSEI of Human.