Decomposition of binary morphological structuring elements based on genetic algorithms

Document Type

Article

Publication Date

8-1-2005

Abstract

Most image processing architectures adapted to morphological operations use structuring elements of a limited size. Various algorithms have been developed for decomposing a large sized structuring element into dilations of small structuring components. However, these decompositions often come with certain restricted conditions. In this paper, we present an improved technique using genetic algorithms to decompose arbitrarily shaped binary structuring elements. The specific initial population, fitness functions, dynamic threshold adaptation, and the recursive size reduction strategy are our features to enhance the performance of decomposition. It can generate the solution in less computational costs, and is suited for parallel implementation. © 2005 Elsevier Inc. All rights reserved.

Identifier

19744366033 (Scopus)

Publication Title

Computer Vision and Image Understanding

External Full Text Location

https://doi.org/10.1016/j.cviu.2005.01.001

ISSN

10773142

First Page

291

Last Page

302

Issue

2

Volume

99

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