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Proceedings Paper

Optical classification of random image fields using spectral synthetic discriminant functions
Author(s): Andrey S. Ostrovsky; Ernesto Pino Mota; Jesus I. Palma Cuatianquiz
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Paper Abstract

It is shown that the problem of classification of images that have the perfectly random nature may be solved with the help of synthetic discriminant functions being synthesized by least-squares technique to separate linearly the power spectra of the corresponding random image fields. The realization of the proposed method by means of an optical technique is discussed, and its efficiency is illustrated by two examples of real-life texture classification.

Paper Details

Date Published: 2 November 2000
PDF: 8 pages
Proc. SPIE 4113, Algorithms and Systems for Optical Information Processing IV, (2 November 2000); doi: 10.1117/12.405841
Show Author Affiliations
Andrey S. Ostrovsky, Benemerita Univ. Autonoma de Puebla (Mexico)
Ernesto Pino Mota, Benemerita Univ. Autonoma de Puebla (Mexico)
Jesus I. Palma Cuatianquiz, Universidad Autonoma de Puebla (Mexico)


Published in SPIE Proceedings Vol. 4113:
Algorithms and Systems for Optical Information Processing IV
Bahram Javidi; Demetri Psaltis, Editor(s)

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