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Proceedings Paper

Dual nonlinear correlation: optoelectronic realization and application to pattern recognition
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Paper Abstract

Dual nonlinear correlation (DNC) is a general operation in optical pattern recognition involving linear and nonlinear filtering methods. Computer controlled DNC processor is based on a two-step optoelectronic joint transform correlator with the power-law nonlinearities introduced in both channels. The DNC optoelectronic processor is sensitive to the value of power-law nonlinearities and can be adapted to the recognition task on various levels of discrimination capability. A CCD camera and a spatial light modulator are the two basic components of the processor that performs the DNC. Their characteristics such as saturation effect and limited number of quantization levels have strong influence on the correlation signal. In this paper we analyze the performance of the DNC processor and present some applications to textured and color pattern recognition with variable discrimination capability.

Paper Details

Date Published: 29 April 1999
PDF: 15 pages
Proc. SPIE 3729, Selected Papers from International Conference on Optics and Optoelectronics '98, (29 April 1999); doi: 10.1117/12.346773
Show Author Affiliations
Katarzyna Chalasinska-Macukow, Warsaw Univ. (Poland)
Rafal Kotynski, Warsaw Univ. (Poland)
Elisabet Perez, Polytechnic Univ. of Catalunya (Spain)
Maria Sagrario Millan Garcia-Verela, Polytechnic Univ. of Catalunya (Spain)

Published in SPIE Proceedings Vol. 3729:
Selected Papers from International Conference on Optics and Optoelectronics '98
Kehar Singh; Om Prakash Nijhawan; Arun Kumar Gupta; A. K. Musla, Editor(s)

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