Template generation for pattern classification
Paul Gader · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1992
A method for combining fuzzy morphological operations with fuzzy logic operations in a heterogeneous network structure is described. The first layer of the network would consist of template operations. The other layers would perform decision making. Such a network could be used to perform classification, image processing functions, and computer vision tasks. Generalized template operations are defmed using image algebra. It is shown that fuzzy morphological operations and linear operations can be obtained from the generalized operations by suitable choices of parameters. Training rules are described that can be used to "learn" the parameters of the generalized operations in a fashion similar to standard backpropagation. Thus, the network could learn linear or morphological operations, or a combination of the two.