Efficient neural network implementation of morphological operations

Aldo Morales; Sung Jea Ko

doi:10.1117/12.58386.full

Efficient neural network implementation of morphological operations

Aldo Morales, Sung Jea Ko

School of Science, Engineering & Technology (Harrisburg)

Research output: Contribution to journal › Conference article › peer-review

4 Scopus citations

Abstract

In this paper we introduce a neural network implementation of gray scale operators. In this structure, synaptic weights are represented by a gray scale structuring element and trained by a learning algorithm based on an optimal criterion called the overall equality index. It will be shown that the proposed algorithm leads to a computationally simple implementation. Numerical examples will be presented to illustrate its performance.

Original language	English (US)
Pages (from-to)	276-286
Number of pages	11
Journal	Proceedings of SPIE - The International Society for Optical Engineering
Volume	1658
DOIs	https://doi.org/10.1117/12.58386.full
State	Published - Apr 1 1992
Event	Nonlinear Image Processing III 1992 - San Jose, United States Duration: Feb 9 1992 → Feb 14 1992

All Science Journal Classification (ASJC) codes

Electronic, Optical and Magnetic Materials
Condensed Matter Physics
Computer Science Applications
Applied Mathematics
Electrical and Electronic Engineering

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Cite this

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abstract = "In this paper we introduce a neural network implementation of gray scale operators. In this structure, synaptic weights are represented by a gray scale structuring element and trained by a learning algorithm based on an optimal criterion called the overall equality index. It will be shown that the proposed algorithm leads to a computationally simple implementation. Numerical examples will be presented to illustrate its performance.",

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AB - In this paper we introduce a neural network implementation of gray scale operators. In this structure, synaptic weights are represented by a gray scale structuring element and trained by a learning algorithm based on an optimal criterion called the overall equality index. It will be shown that the proposed algorithm leads to a computationally simple implementation. Numerical examples will be presented to illustrate its performance.

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U2 - 10.1117/12.58386.full

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M3 - Conference article

AN - SCOPUS:0042316542

SN - 0277-786X

VL - 1658

SP - 276

EP - 286

JO - Proceedings of SPIE - The International Society for Optical Engineering

JF - Proceedings of SPIE - The International Society for Optical Engineering

T2 - Nonlinear Image Processing III 1992

Y2 - 9 February 1992 through 14 February 1992

ER -

Efficient neural network implementation of morphological operations

Abstract

All Science Journal Classification (ASJC) codes

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