Maximum-Likelihood Image Classification
Miles N. Wernick, G. Michael Morris · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1988
An essential feature of a practical automatic image recognition system is the ability to tolerate certain types of variations within images. The recognition of images subject to intrinsic variations can be treated as a sorting task in which an image is identified as a member of some class of images. Herein, the maximum-likelihood strategy, an important tool in the field of statistical decision theory, is applied to the image classification problem. We show that the strategy can be implemented in a standard image correlation system and that excellent classification results can be obtained.