Titlebook: Variational and Level Set Methods in Image Segmentation; Amar Mitiche,Ismail Ben Ayed Book 2011 Springer-Verlag Berlin Heidelberg 2011 Flo

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Region Merging Priors,nd. In the methods we examined so far, the number of regions occurs as a constant in the objective functional and its optimization. How to allow it to vary is an important question which has been generally avoided. A few studies have considered determining the number of regions automatically, either

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Motion Based Image Segmentation, at each point of the retinal image domain. Nakayama and Loomis [2] referred to optical flow later as the . over the image positional domain and provided an analytic working definition of ., the instantaneous velocity vector. In this book, we will retain the essence of Gibson’s and Nakayama’s defini

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Image Segmentation According to the Movement of Real Objects,ore, the model parameters served to distinguish the segmentation regions. We presented two methods which differed by their representation of the segmentation boundaries. One of the methods (Chapter 7, Section 7.2) can be viewed as an optical flow edge detection method. It used the minimum descriptio

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Book 2011gions. Therefore, segmenting an image is to divide its domain into relevant components. The efficient solution of the key problems in image segmentation promises to enable a rich array of useful applications. The current major application areas include robotics, medical image analysis, remote sensin

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Variational and Level Set Methods in Image Segmentation

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1866-2609 then derived and solved numerically. The book covers, within the active curve and level set formalism, the basic two-region segmentation methods, multiregion extensions, re978-3-642-26562-4978-3-642-15352-5Series ISSN 1866-2609 Series E-ISSN 1866-2617

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