Applications of stochastic geometry in image analysis

M.N.M. Lieshout, van

Research output: Chapter in Book/Report/Conference proceedingChapterAcademic

1 Citation (Scopus)

Abstract

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.
Original languageEnglish
Title of host publicationNew perspectives in stochastic geometry
EditorsW.S. Kendall, I.S. Molchanov
Place of PublicationOxford
PublisherOxford University Press
Pages427-450
ISBN (Print)978-0-19-923257-4
Publication statusPublished - 2009

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    Lieshout, van, M. N. M. (2009). Applications of stochastic geometry in image analysis. In W. S. Kendall, & I. S. Molchanov (Eds.), New perspectives in stochastic geometry (pp. 427-450). Oxford University Press.