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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Vydáno v:	Multimedia tools and applications Ročník 79; číslo 25-26; s. 18839 - 18858
Hlavní autoři:	Dhanachandra, Nameirakpam, Chanu, Yambem Jina
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	New York Springer US 01.07.2020 Springer Nature B.V
Témata:	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
On-line přístup:	Získat plný text
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