Title
Decomposition of binary morphological structuring elements based on genetic algorithms
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.
Year
DOI
Venue
2005
10.1016/j.cviu.2005.01.001
Computer Vision and Image Understanding
Keywords
DocType
Volume
small structuring component,genetic algorithm,recursive size reduction strategy,fitness function,Mathematical morphology,Genetic algorithms,Decomposition,binary morphological,dynamic threshold adaptation,limited size,Structuring element,image processing,certain restricted condition,computational cost,binary structuring element
Journal
99
Issue
ISSN
Citations 
2
Computer Vision and Image Understanding
6
PageRank 
References 
Authors
0.57
8
2
Name
Order
Citations
PageRank
Frank Y. Shih1110389.56
Yi-Ta Wu233131.22