30 June 1994 Adaptive resonance theory and self-organizing morphological kernels
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Abstract
In this paper we describe our recent work developing automated methods for generation of kernels or structuring elements for use in the hit-or-miss transform. We show how a neural network algorithm (Fuzzy Adaptive Resonance Theory) generates hit and miss structuring elements that can be used with a fuzzy morphology to detect a class of objects and we illustrate with computer simulations.
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John P. Sharpe, Nilgun Sungar, Kristina M. Johnson, "Adaptive resonance theory and self-organizing morphological kernels", Proc. SPIE 2300, Image Algebra and Morphological Image Processing V, (30 June 1994); doi: 10.1117/12.179210; https://doi.org/10.1117/12.179210
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