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Proceedings Paper

Neural network implementation of mathematical morphology operation
Author(s): Peng Tao; Jie-Gu Li
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Paper Abstract

This paper proposes a feedforward neural network structure to realize the mathematical morphology operations (MMO), namely: HMT (Hit and Miss Transformation), dilation, erosion, opening, closing, and the union and intersection (for multistructuring elements and multioperators) of them. Different kinds of operations can be implemented by assigning the weights, the threshold values and the architecture of the network according to the operation itself to be implemented. A general expression relating the weight value, threshold value to the configuration of the structuring element for different operations is derived, the assigning of the values becomes merely straight-forward training procedure of the proposed network. Also, it is proved that with a single hidden layer, all the MMO can be implemented by the ANN. The most interesting aspect of the method proposed is the reduction of on-line operation steps, which for conventional MMO algorithm consist of a series of operations processed consecutively. As a extension of the method, Boolean function implementations of the operations are also proposed, in which, the concept of collection of basic `And' structuring elements is presented. We prove that all MMO sequence can be implemented by a 2-layer logic gate array (or 3 layers in the sense of node levels).

Paper Details

Date Published: 2 March 1994
PDF: 12 pages
Proc. SPIE 2243, Applications of Artificial Neural Networks V, (2 March 1994); doi: 10.1117/12.169964
Show Author Affiliations
Peng Tao, Shanghai Jiao-tong Univ. (China)
Jie-Gu Li, Shanghai Jiao-tong Univ. (China)

Published in SPIE Proceedings Vol. 2243:
Applications of Artificial Neural Networks V
Steven K. Rogers; Dennis W. Ruck, Editor(s)

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