| 摘要 |
PROBLEM TO BE SOLVED: To classify feature vectors extracted from image data by clustering by specifying the level of optimal classification matching inputted image data from the image data themselves without the need of inputting any parameter to designate the level of desired classification. SOLUTION: A plurality of low resolution images whose resolutions are different stepwise are derived from an original image, and the initial representative vectors of two or more clusters are derived from the lowest resolution image whose resolution is the lowest. The optimal classification of feature vectors in the respective low resolution images is successively derived while increasing the representative vectors on which information in a real image space is reflected on the basis of the correlation of the classification of image areas in the real image space and the classification in a feature vector space by using those initial representative vectors, and finally the optimal classification of the feature vectors extracted from the individual pixels of the original image is derived. COPYRIGHT: (C)2004,JPO&NCIPI
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