Similar-image retrieval systems using ICA and PCA bases

Similar-image retrieval systems are presented and evaluated. The new systems directly use image bases via ICA (independent component analysis) and PCA (principal component analysis). These bases can extract source image´s information which is viable to define similarity measures. But, the indeterminacy on amplitude and permutation exists. In this paper, similarity measures which can absorb such indeterminacy are presented. Then, carefully designed opinion tests are carried out to compare the new systems´ ability with existing ones. The compatibility of color spaces such as RGB, YIQ, and HSV is also examined. By these massive tests, {ICA, HSV} is judged the best. The resulting system is thus proved to be highly competent at the similar-image retrieval.