Hybrid Soft Computing for Multilevel Image and Data Segmentation

This book explains efficient solutions for segmenting the intensity levels of different types of multilevel images. The authors present hybrid soft computing techniques, which have advantages over conventional soft computing solutions as they incorporate data heterogeneity into the clustering/segmen...

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Détails bibliographiques
Cote:Libro Electrónico
Auteurs principaux: De, Sourav (Auteur), Bhattacharyya, Siddhartha (Auteur), Chakraborty, Susanta (Auteur), Dutta, Paramartha (Auteur)
Collectivité auteur: SpringerLink (Online service)
Format: Électronique eBook
Langue:Inglés
Publié: Cham : Springer International Publishing : Imprint: Springer, 2016.
Édition:1st ed. 2016.
Collection:Computational Intelligence Methods and Applications,
Sujets:
Artificial intelligence.
Computational intelligence.
Image processing-Digital techniques.
Computer vision.
Artificial Intelligence.
Computational Intelligence.
Computer Imaging, Vision, Pattern Recognition and Graphics.
Accès en ligne:Texto Completo
Description
Résumé:This book explains efficient solutions for segmenting the intensity levels of different types of multilevel images. The authors present hybrid soft computing techniques, which have advantages over conventional soft computing solutions as they incorporate data heterogeneity into the clustering/segmentation procedures. This is a useful introduction and reference for researchers and graduate students of computer science and electronics engineering, particularly in the domains of image processing and computational intelligence.
Description matérielle:XIV, 235 p. 99 illus., 39 illus. in color. online resource.
ISBN:9783319475240
ISSN:2510-1773

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