An image segmentation approach based on fuzzy c-means and dynamic particle swarm optimization algorithm

Image segmentation has considered an important step in image processing. Fuzzy c-means (FCM) is one of the commonly used clustering algorithms because of its simplicity and effectiveness. However, FCM has the disadvantages of sensitivity to initial values, falling easily into local optimal solution...

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Bibliographic Details
Published in:	Multimedia tools and applications Vol. 79; no. 25-26; pp. 18839 - 18858
Main Authors:	Dhanachandra, Nameirakpam, Chanu, Yambem Jina
Format:	Journal Article
Language:	English
Published:	New York Springer US 01.07.2020 Springer Nature B.V
Subjects:	Algorithms Clustering Computer Communication Networks Computer Science Data Structures and Information Theory Global optimization Image enhancement Image processing Image segmentation Inertia Learning Literature reviews Magnetic resonance imaging Multimedia Information Systems Noise Noise reduction Noise sensitivity Optimization Parameters Particle swarm optimization Special Purpose and Application-Based Systems Weight Image segmentation Dynamic particle swarm optimization Clustering MRI image Fuzzy c-means
ISSN:	1380-7501, 1573-7721
Online Access:	Get full text
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