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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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書目名稱Variational and Level Set Methods in Image Segmentation
編輯Amar Mitiche,Ismail Ben Ayed
視頻videohttp://file.papertrans.cn/981/980628/980628.mp4
概述Useful applications in remote sensing, medicine.Useful applications in robotics, database search.Useful applications in security.Includes supplementary material:
叢書名稱Springer Topics in Signal Processing
圖書封面Titlebook: Variational and Level Set Methods in Image Segmentation;  Amar Mitiche,Ismail Ben Ayed Book 2011 Springer-Verlag Berlin Heidelberg 2011 Flo
描述Image segmentation consists of dividing an image domain into disjoint regions according to a characterization of the image within or in-between the regions. 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 sensing, scene understanding, and image database retrieval. The subject of this book is image segmentation by variational methods with a focus onformulations which use closed regular plane curves to define the segmentation regions and on a level set implementation of the corresponding active curve evolution algorithms. Each method is developed from an objective functional which embeds constraints on both the image domain partition of the segmentation and the image data within or in-between the partition regions. The necessary conditions to optimize the objective functional are then derived and solved numerically. The book covers, within the active curve and level set formalism, the basic two-region segmentation methods, multiregion extensions, re
出版日期Book 2011
關鍵詞Flow Estimation; Image Models; Optical Flow 3D segmentaion
版次1
doihttps://doi.org/10.1007/978-3-642-15352-5
isbn_softcover978-3-642-26562-4
isbn_ebook978-3-642-15352-5Series ISSN 1866-2609 Series E-ISSN 1866-2617
issn_series 1866-2609
copyrightSpringer-Verlag Berlin Heidelberg 2011
The information of publication is updating

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Image Models,scriptions which distinguish each region from the others. The descriptions validity largely affects the segmentation accuracy, i.e., the descriptions must fit the class of images to segment. In this chapter, we will examine various statistical descriptions in active curve image segmentation and map each to a curve evolution equation.
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Variational and Level Set Methods in Image Segmentation978-3-642-15352-5Series ISSN 1866-2609 Series E-ISSN 1866-2617
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Amar Mitiche,Ismail Ben AyedUseful applications in remote sensing, medicine.Useful applications in robotics, database search.Useful applications in security.Includes supplementary material:
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Springer Topics in Signal Processinghttp://image.papertrans.cn/v/image/980628.jpg
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