Kernel Based Fuzzy Clustering by Kaur Prabhjot (4 results)

Paperback. Condition: Brand New. 116 pages. 8.66x5.91x0.27 inches. In Stock.

Taschenbuch. Condition: Neu. Kernel based Fuzzy Clustering for Robust Image Segmentation | A Review and Comparison | Prabhjot Kaur (u. a.) | Taschenbuch | Englisch | LAP Lambert Academic Publishing | EAN 9783659281600 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. …

Kartoniert / Broschiert. Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Kaur PrabhjotPrabhjot Kaur, working as a Reader in Information Technology Department, Maharaja Surajmal Institute of Technology, Guru Gobind Singh Indraprastha University, New Delhi, India. Her research areas include soft Computing t.…

Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - 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.…