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COMPUTATION OF MINKOWSKI MEASURES ON 2D AND 3D BINARY IMAGES
Author(s) -
David Legland,
Kiên Kiêu,
Marie-Françoise Devaux
Publication year - 2011
Publication title -
image analysis and stereology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.237
H-Index - 27
eISSN - 1854-5165
pISSN - 1580-3139
DOI - 10.5566/ias.v26.p83-92
Subject(s) - minkowski space , minkowski addition , mathematics , computation , measure (data warehouse) , convergence (economics) , minkowski's theorem , binary number , image (mathematics) , algorithm , computer science , geometry , arithmetic , artificial intelligence , data mining , economics , economic growth
Minkowski functionals encompass standard geometric parameters such as volume, area, length and the Euler-Poincaré characteristic. Software tools for computing approximations of Minkowski functionals on binary 2D or 3D images are now available based on mathematical methods due to Serra, Lang and Ohser. Minkowski functionals can not be used to describe spatial heterogeneity of structures. This description can be performed by using Minkowski measures, which are local versions of Minkowski functionals. In this paper, we discuss how to extend the computation of Minkowski functionals to the computation of Minkowski measures. Approximations of Minkowski measures are computed using fltering and look-up table transformations. The final result is represented as a grey-level image. Approximation errors are investigated based on numerical examples. Convergence and non convergence of the measure approximations are discussed. The measure of surface area is used to describe spatial heterogeneity of a synthetic structure, and of an image of tomato pericarp

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