[OPTICAL REVIEW Vol. 5, No. 4 (1998) 219-225]

Classification of Random Image Fields Using Synthetic Discriminant Functions: Spectral Statistical Approach and Its Computer-Optical Realization

Andrey S. OSTROVSKY and Ernesto PINO-MOTA

Facultad de Ciencias FE½ico Matem疸icas, Benem駻ita Universidad Autû¥¢oma de Puebla, 72570, Puebla, Pue., M騙ico

(Received February 6, 1998; Accepted May 18, 1998)

The problem of classification of images that have a perfectly random nature is considered. We propose a new approach to solve this problem that is based on the use of the synthetic discriminant functions being synthesized to separate linearly the power spectra of random image fields to be classified. In the stage of both discriminant function synthesis and classification, the statistical technique of power spectrum estimation is employed. The realization of the proposed approach by means of a hybrid computer-optical technique is discussed, and its effciency is illustrated by two examples of real-world texture classification.

Key words : image classification, random image field, power spectrum, synthetic discriminant function, statistical estimation, Fourier-optical technique

andreyo@fcfm.buap.mx

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