by Thomas Illetschko
Abstract:
Combinatorial maps and irregular pyramids based on combinatorial maps for 2D data have been studied in great detail. It has been shown that this concept is advantageous for many applications in the field of image processing and pattern recognition by providing means to store information of the topological relation of the represented data. While the concept of combinatorial maps has been defined for any dimension, most of the studies concentrated on the representation of two dimensional data and only few results exist regarding higher dimensions. This report studies the properties of combinatorial maps for 3D data. Especially collapsing an initial map of the volumetric data by applying contraction and removal operations to produce a minimal representation while preserving the topological relations is presented in this report. Formal conditions for applying these operations as well as the minimal configurations of the topological relations found in volumetric data are presented in this report and means for discriminating and identifying these minimal configurations using pseudo elements are introduced.
Reference:
Minimal Combinatorial Maps for analyzing 3D Data (Thomas Illetschko), Technical report, PRIP, TU Wien, 2006.
Bibtex Entry:
@TechReport{TR110,
author = "Thomas Illetschko",
title = "Minimal Combinatorial Maps for analyzing 3D Data",
institution = "PRIP, TU Wien",
number = "PRIP-TR-110",
year = "2006",
url = "https://www.prip.tuwien.ac.at/pripfiles/trs/tr110.pdf",
abstract = "Combinatorial maps and irregular pyramids based on
combinatorial maps for 2D data have been studied in
great detail. It has been shown that this concept is
advantageous for many applications in the field of
image processing and pattern recognition by
providing means to store information of the
topological relation of the represented data. While
the concept of combinatorial maps has been defined
for any dimension, most of the studies concentrated
on the representation of two dimensional data and
only few results exist regarding higher
dimensions. This report studies the properties of
combinatorial maps for 3D data. Especially
collapsing an initial map of the volumetric data by
applying contraction and removal operations to
produce a minimal representation while preserving
the topological relations is presented in this
report. Formal conditions for applying these
operations as well as the minimal configurations of
the topological relations found in volumetric data
are presented in this report and means for
discriminating and identifying these minimal
configurations using pseudo elements are
introduced.",
}