Database retrieval for similar images using ICA and PCA bases

Naoto Katsumata*, Yasuo Matsuyama


    研究成果: Article査読

    38 被引用数 (Scopus)


    Similar-image retrieval systems are newly presented and examined. The systems use ICA bases (independent component analysis bases) or PCA bases (principal component analysis bases). These bases can contain source image's information, however, the indeterminacy of ordering and amplitude on the bases exists due to the PCA and ICA problem formulation per se. But, this paper successfully avoids this difficulty by using weighted inner products of similar bases. A set of opinion test is carried out on 18 systems according to the combination of {similarity measures (ICA, PCA, color histogram), color spaces (RGB, YIQ, HSV), filtering (with, without)}. The color histogram method is a traditional method. The opinion test shows that the presented method of {ICA, HSV, without filtering} is the best. Runners-up are {ICA, HSV or RGB or YIQ, with filtering}. The traditional method is judged to be much inferior. Thus, this paper's method is found quite effective to the similar-image retrieval from large databases.

    ジャーナルEngineering Applications of Artificial Intelligence
    出版ステータスPublished - 2005 9月

    ASJC Scopus subject areas

    • 人工知能
    • 制御およびシステム工学


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