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24 May 2000 Pattern recognition based on binary decompositions: the optical morphological correlation
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Proceedings Volume 4089, Optics in Computing 2000; (2000) https://doi.org/10.1117/12.386801
Event: 2000 International Topical Meeting on Optics in Computing (OC2000), 2000, Quebec City, Canada
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.
© (2000) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Pascuala Garcia-Martinez "Pattern recognition based on binary decompositions: the optical morphological correlation", Proc. SPIE 4089, Optics in Computing 2000, (24 May 2000); doi: 10.1117/12.386801; https://doi.org/10.1117/12.386801
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