Defining optimal feature sets for segmentation by statistical pattern recognition
James M. Coggins, Chang-Hua Huang · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1993
A methodology for task-sensitive pixel classification is defined based on multiscale Gaussian derivatives and statistical pattern recognition methods. Multiscale Gaussian derivatives are approximated by Gaussian and offset-Gaussian filters to decrease computational requirements. A method is devised for computing a discriminant vector between classes based on class isolation and compactness. The optimal discriminant vector is converted back into image form and applied to the image to determine whether a 1-D feature space is adequate to separate the classes.