0000000000880809
AUTHOR
Manuel Tejera
Weighted nonlinear correlation for controlled discrimination capability
We recently demonstrated the high discrimination capability as well as the high sensitivity to small intensity variations of the sliced orthogonal nonlinear generalized (SONG) correlation. This nonlinear correlation has a correlation matrix representation. Previous papers considered only the principal diagonal elements of the correlation matrix. We propose using the off-diagonal non-zero elements of the SONG correlation matrix in order to achieve variable discrimination performance and controlled detection adapted to the gray-scale variations. Moreover, we introduce negative coefficients in order to improve the discrimination properties of the SONG correlation. To control the degree of reco…
Optical implementation of the weighted sliced orthogonal nonlinear generalized correlation for nonuniform illumination conditions.
Optical pattern recognition under variations of illumination is an important issue. The sliced orthogonal nonlinear generalized (SONG) correlation has been proposed as an optical pattern recognition tool to discriminate with high efficiency between objects. But, at the same time, the SONG correlation is very sensitive to gray-scale image variations. In a previous work, we expanded the definition of the SONG correlation to the Weighted SONG (WSONG) correlation to modify the discrimination capability in a controlled way. Here, we propose to use the WSONG when pattern recognition is obtained by means of optical correlation under nonuniform illumination. The calculation of the WSONG correlation…