Applications of stochastic geometry in image analysis

M.N.M. Lieshout, van

Research output: Chapter in Book/Report/Conference proceedingChapterAcademic

1 Citation (Scopus)


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
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.