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Performance Improvement of Image Retrieval System by Presenting Query based on Human Perception  

유헌우 (연세대학교 인지과학연구소)
장동식 (고려대학교 산업시스템정보공학과)
오근태 (수원대학교 산업정보공학과)
Publication Information
Journal of KIISE:Computing Practices and Letters / v.9, no.2, 2003 , pp. 158-165 More about this Journal
Abstract
Image similarity is often decided by computing the distance between two feature vectors. Unfortunately, the feature vector cannot always reflect the notion of similarity in human perception. Therefore, most current image retrieval systems use weights measuring the importance of each feature. In this paper new initial weight selection and update rules are proposed for image retrieval purpose. In order to obtain the purpose, database images are first divided into groups based on human perception and, inner and outer query are performed, and, then, optimal feature weights for each database images are computed through searching the group where the result images among retrieved images are belong. Experimental results on 2000 images show the performance of proposed algorithm.
Keywords
image retrieval; optimal feature weight; human perception; grouping;
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