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New Perspectives in Stochastic Geometry$
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Wilfrid S. Kendall and Ilya Molchanov

Print publication date: 2009

Print ISBN-13: 9780199232574

Published to Oxford Scholarship Online: February 2010

DOI: 10.1093/acprof:oso/9780199232574.001.0001

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PRINTED FROM OXFORD SCHOLARSHIP ONLINE (oxford.universitypressscholarship.com). (c) Copyright Oxford University Press, 2021. All Rights Reserved. An individual user may print out a PDF of a single chapter of a monograph in OSO for personal use. date: 27 October 2021

Applications of Stochastic Geometry in Image Analysis

Applications of Stochastic Geometry in Image Analysis

Chapter:
(p.427) 13 Applications of Stochastic Geometry in Image Analysis
Source:
New Perspectives in Stochastic Geometry
Author(s):

Marie‐Colette N.M. van Lieshout

Publisher:
Oxford University Press
DOI:10.1093/acprof:oso/9780199232574.003.0013

A discussion is given of various stochastic geometry models (random fields, sequential object processes, polygonal field models) which can be used in intermediate‐ and high‐level image analysis. Two examples are presented of actual image analysis problems (motion tracking in video, foreground/background separation) to which these ideas can be applied.

Keywords:   random fields, sequential object processes, polygonal field models, motion tracking, foreground separation, background separation

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