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Optical Engineering

Learning optimization of morphological filters with gray scale structuring elements
Author(s): Akira Asano; Tohru Yamashita; Shunsuke Yokozeki
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Paper Abstract

Mathematical morphology with gray scale structuring elements has attracted much attention, since combinations of the operations in this class can realize almost all noise-removing filters. However, the optimization method for the combination is still uncertain. In this paper, an optimization method for a mathematical morphological filter with gray scale structuring elements is proposed. This method is based on the concept of a neural network with morphological operations and on learning using simulated annealing. The method is also applied to gray scale bipolar morphological filters for image differentiation.

Paper Details

Date Published: 1 August 1996
PDF: 11 pages
Opt. Eng. 35(8) doi: 10.1117/1.600827
Published in: Optical Engineering Volume 35, Issue 8
Show Author Affiliations
Akira Asano, Kyushu Institute of Technology (Japan)
Tohru Yamashita, Kyushu Institute of Technology (Japan)
Shunsuke Yokozeki, Kyushu Institute of Technology (Japan)

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