An Overview of PSO- Based Approaches in Image Segmentation

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Author(s) Amanpreet Kaur | M.D. Singh
Pages 1349-1357
Volume 2
Issue 8
Date August, 2012
Keywords Particle swarm optimization, Image segmentation, Thresholding, Fuzzy system, Genetic algorithm, Wavelets, Clustering, Rough set, Neural network

Abstract

Particle swarm optimization (PSO) is recent approach that can be employed in a wide range of applications. It is an evolutionary computing method based on colony aptitude which is a better parallel searching algorithm. Image segmentation is a low level vision task which is applicable in various applications such as object recognition, medical imaging, document analysis, just to name a few. PSO itself is a very powerful technique and when combined with other computational intelligence technique results in a truly affected approach. In this paper we have reviewed how PSO can be combined with various other methodologies such as neural networks, rough sets, clustering, thresholding, genetic algorithm, wavelets and fuzzy systems.

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