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Kernel based Fuzzy Clustering for Robust Image Segmentation - Prabhjot Kaur
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Prabhjot Kaur:
Kernel based Fuzzy Clustering for Robust Image Segmentation - Livres de poche

ISBN: 9783659281600

[ED: Taschenbuch], [PU: LAP Lambert Academic Publishing], 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., DE, [SC: 2.00], Neuware, gewerbliches Angebot, 220x150x7 mm, 116, [GW: 189g], PayPal, offene Rechnung, Banküberweisung, sofortueberweisung.de, Interntationaler Versand

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Kernel based Fuzzy Clustering for Robust Image Segmentation : A Review and Comparison - Prabhjot Kaur
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Prabhjot Kaur:
Kernel based Fuzzy Clustering for Robust Image Segmentation : A Review and Comparison - Livres de poche

2012, ISBN: 3659281603

ID: 22516629865

[EAN: 9783659281600], Neubuch, [PU: LAP Lambert Academic Publishing Okt 2012], This item is printed on demand - Print on Demand 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

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AHA-BUCH GmbH, Einbeck, Germany [51283250] [Rating: 5 (von 5)]
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Kernel based Fuzzy Clustering for Robust Image Segmentation - Kaur, Prabhjot / Sharma, Poonam
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Kaur, Prabhjot / Sharma, Poonam:
Kernel based Fuzzy Clustering for Robust Image Segmentation - Livres de poche

ISBN: 3659281603

ID: 22517553545

[EAN: 9783659281600], Neubuch, Publisher/Verlag: LAP Lambert Academic Publishing | A Review and Comparison | 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. | Format: Paperback | Language/Sprache: english | 116 pp

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Kernel based Fuzzy Clustering for Robust Image Segmentation als Buch von Prabhjot Kaur, Poonam Sharma, Pallavi Gupta - LAP Lambert Academic Publishing
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LAP Lambert Academic Publishing:
Kernel based Fuzzy Clustering for Robust Image Segmentation als Buch von Prabhjot Kaur, Poonam Sharma, Pallavi Gupta - nouveau livre

ISBN: 9783659281600

ID: 820100258

Kernel based Fuzzy Clustering for Robust Image Segmentation ab 49 EURO A Review and Comparison Kernel based Fuzzy Clustering for Robust Image Segmentation ab 49 EURO A Review and Comparison Bücher > English, International > Gebundene Ausgaben

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Kernel based Fuzzy Clustering for Robust Image Segmentation: A Review and Comparison - Prabhjot Kaur; Poonam Sharma; Pallavi Gupta
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Prabhjot Kaur; Poonam Sharma; Pallavi Gupta:
Kernel based Fuzzy Clustering for Robust Image Segmentation: A Review and Comparison - Livres de poche

2012, ISBN: 3659281603

ID: 22412584244

[EAN: 9783659281600], Neubuch, [PU: Lap Lambert Academic Publishing], This item is printed on demand for shipment within 3 working days.

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European-Media-Service Mannheim, Mannheim, Germany [1048135] [Rating: 5 (von 5)]
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