Parallel genetic algorithms for optimizing morphological filters

Several design methods for parallel genetic algorithms (PGAs) optimizing morphological filters are discussed and an optimal scale and machine independent PGA for a loosely coupled, homogeneous or inhomogeneous multiprocessor computer is developed. The optimization is made in terms of computation spe...

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Bibliographic Details
Published in:Fifth International Conference on Image Processing and its Applications pp. 762 - 766
Main Authors: Kraft, P, Marshall, S, Soraghan, J.J, Harvey, N.R
Format: Conference Proceeding
Language:English
Published: London IEE 1995
Subjects:
Computer vision and image processing techniques
Optical information, image and video signal processing
Optimisation techniques
Parallel programming and algorithm theory
Pattern recognition
image processing
parallel algorithms
parallelization efficiency
parallel genetic algorithms
multiprocessor computer
best chromosome fit
genetic algorithms
design methods
quality
optimisation
performance
optimization
morphological filters
computation speed
digital filters
mathematical morphology
ISBN:0852966423, 9780852966426
Online Access:Get full text
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Summary:Several design methods for parallel genetic algorithms (PGAs) optimizing morphological filters are discussed and an optimal scale and machine independent PGA for a loosely coupled, homogeneous or inhomogeneous multiprocessor computer is developed. The optimization is made in terms of computation speed, parallelization efficiency and quality. Quality means, in this context, the fitness of the best chromosome, which is an objective measure for the performance of the corresponding morphological filter in a particular environment.
ISBN:0852966423
9780852966426
DOI:10.1049/cp:19950762