| Budget Amount *help |
¥3,200,000 (Direct Cost: ¥3,200,000)
Fiscal Year 2003: ¥900,000 (Direct Cost: ¥900,000)
Fiscal Year 2002: ¥2,300,000 (Direct Cost: ¥2,300,000)
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| Research Abstract |
A rapid algorithm of searching for similar images to an object image in a set of registered images is proposed. The set of images is assumed to be processed to have correlation coefficients for all the pairs of registered images in advance and in offline. For designing the algorithm, by an indirect way through any pivot image, we mathematically derive a constraint inequality about correlation coefficients between any registered images and the object image provided. The inequality shows a range of values of estimated correlation coefficients for unknown registered images. Mainly by use of the upper bounds defined by the inequality, three conditions for selecting redundant or neglected images having small similarity from the total image set can be derived, which enable to quicken computation of searching. The rapid algorithm is applied to real world searching problems with the set of 1,200 images of Japanese characters, Hirakana. Efficiency rate of eight times in average could be obtained for searching 204 object images of various similarities, enabling to show the effectiveness of the proposed method for real world tasks of image retrieval in large scale image database systems, media database, and data mining systems. The proposed algorithm can be applied for decreasing computational cost in cooperation with some existing schemes, such as SSDA, and random sampling.
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