This book develops the stochastic geometry framework for image analysis purpose. Two main frameworks are described: marked point process and random closed sets models. We derive the main issues for defining an appropriate model. The algorithms for sampling and optimizing the models as well as for estimating parameters are reviewed. Editor(s): Descombes, Xavier. Num Pages: 356 pages, Illustrations. BIC Classification: TJ. Category: (P) Professional & Vocational. Dimension: 235 x 163 x 25. Weight in Grams: 684. . 2011. . . . . Books ship from the US and Ireland.

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T�tulo: Stochastic Geometry for Image Analysis
Editor: ISTE Ltd and John Wiley & Sons Inc
Fecha de publicaci�n: 2011
Idioma: Ingl�s
ISBN 10: 1848212402
ISBN 13: 9781848212404
Encuadernaci�n: Encuadernaci�n de tapa dura
Estado: New

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Sinopsis

This book develops the stochastic geometry framework for image analysis purpose. Two main frameworks are described: marked point process and random closed sets models. We derive the main issues for defining an appropriate model. The algorithms for sampling and optimizing the models as well as for estimating parameters are reviewed. Numerous applications, covering remote sensing images, biological and medical imaging, are detailed. This book provides all the necessary tools for developing an image analysis application based on modern stochastic modeling.

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Xavier Descombes, Director of Research INRIA, EPI Ariana

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