Vector morphology and iconic neural networks

Mathematical morphology involves the geometrical analysis of shapes and textures in images. Methods of generalizing morphology are presented, and it is shown that all common image-based operators are instances of two fundamental operators where voting logic is at a pivotal point. Another generalization leads to vector operators. A sequence of vector morphology operations is similar to a multiple-layer iconic neural network. In morphology, a new operator called a weighted rank order filter becomes apparent. It is noted that massively parallel, bit serial computer architectures are the most effective way to realize the various operations discussed. >

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