ISBN: 9783659281600

[ED: Taschenbuch], [PU: LAP Lambert Academic Publishing], The goal of image segmentation is partitioning of an image into a set of disjoint regions with uniform and homogeneous attributes… Plus…

[ED: Taschenbuch], [PU: LAP Lambert Academic Publishing], 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..., DE, [SC: 0.00], Neuware, gewerbliches Angebot, 116, Banküberweisung, PayPal, [CT: Sonstiges / Sonstiges]<

2012, ISBN: 3659281603

[EAN: 9783659281600], Neubuch, [PU: LAP Lambert Academic Publishing], nach der Bestellung gedruckt Neuware - Printed after ordering - The goal of image segmentation is partitioning of an … Plus…

[EAN: 9783659281600], Neubuch, [PU: LAP Lambert Academic Publishing], 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., Books<

2012, ISBN: 3659281603

[EAN: 9783659281600], Neubuch, [PU: LAP Lambert Academic Publishing], This item is printed on demand - it takes 3-4 days longer - Neuware -The goal of image segmentation is partitioning o… Plus…

[EAN: 9783659281600], Neubuch, [PU: LAP Lambert Academic Publishing], This item is printed on demand - it takes 3-4 days longer - Neuware -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. 116 pp. Englisch, Books<

ISBN: 9783659281600

Paperback, [PU: LAP Lambert Academic Publishing], The goal of image segmentation is partitioning of an image into a set of disjoint regions with uniform and homogeneous attributes such as… Plus…

Paperback, [PU: LAP Lambert Academic Publishing], 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.<

2012, ISBN: 3659281603

[EAN: 9783659281600], Neubuch, [PU: LAP Lambert Academic Publishing], ALLGEMEINE UND VERGLEICHENDE LITERATURWISSENSCHAFT, Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihre… Plus…

[EAN: 9783659281600], Neubuch, [PU: LAP Lambert Academic Publishing], ALLGEMEINE UND VERGLEICHENDE LITERATURWISSENSCHAFT, Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. 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, Books<