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Proceedings Paper

Pattern recognition based on binary decompositions: the optical morphological correlation
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Paper Abstract

Optical pattern recognition can be improved using powerful filters or defining new correlations. The morphological correlation is a robust detection method that minimizes the mean absolute error between two patterns. The morphological correlation is a nonlinear correlation and it is defined as the average over all the amplitudes of the linear correlation between thresholded versions of the input scene and the reference object for every gray level. This nonlinear correlation can be implemented optically using a joint transform correlator and provides higher performance and higher discrimination abilities in comparison with other linear correlation methods. We define different morphological correlations using different binary decompositions. Those correlations allow efficient pattern recognition with higher discrimination ability than other common linear image detection techniques. Experimental result will be presented.

Paper Details

Date Published: 24 May 2000
PDF: 10 pages
Proc. SPIE 4089, Optics in Computing 2000, (24 May 2000); doi: 10.1117/12.386801
Show Author Affiliations
Pascuala Garcia-Martinez, Univ. de Valencia (Spain)

Published in SPIE Proceedings Vol. 4089:
Optics in Computing 2000
Roger A. Lessard; Tigran V. Galstian, Editor(s)

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