Kernel based Fuzzy Clustering for Robust Image Segmentation: A Review and Comparison - Softcover

Kaur, Prabhjot; Sharma, Poonam; Gupta, Pallavi

Softcover

ISBN 10: 3659281603 ISBN 13: 9783659281600

Verlag: LAP LAMBERT Academic Publishing, 2012

Inhaltsangabe

The goal of image segmentation is partitioning of an image into a set of disjoint regions with uniform and homogeneous attributes such as intensity, color, tone etc. Image Segmentation plays an important role in a variety of applications like robot vision, object recognition, pattern recognition, image segmentation etc. Real digital Images generally contain unknown noise and considerable uncertainty. Although the Fuzzy C Means (FCM) algorithm functions well on noiseless images but it fails to segment images when corrupted with noise. To overcome this problem this book discussed well-known “kernel methods” that have been applied for noisy image segmentation. This book analysed the performance of the four algorithms FCM, Kernelized FCM (KFCM), Kernelized Intuitionistic FCM (KIFCM), Kernelized Type-2 FCM (K2FCM) with four synthetic images in noiseless case as well as when the images are corrupted with salt & pepper and Gaussian noise. The four algorithms are studied and analysed both qualitatively and quatitatively.

Details zur Ausgabe

• Verlag: LAP LAMBERT Academic Publishing
• Erscheinungsdatum: 2012
• Sprache: Englisch
• ISBN 10: 3659281603
• ISBN 13: 9783659281600
• Einband: Taschenbuch
• Anzahl der Seiten: 116
• Kontakt zum Hersteller: Nicht verfügbar
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