[Zurück]

H. Molina-Abril, P. Real:
"Homological Spanning Forest framework for 2D image processing";
Annals of Mathematics and Artificial Intelligence, 64 (2012), 4; S. 385 - 409.

A 2D topology-based digital image processing framework is presented
here. This framework consists of the computation of a flexible geometric graphbased
structure, starting from a raster representation of a digital image I. This
structure is called Homological Spanning Forest (HSF for short), and it is built
on a cell complex associated to I. The HSF framework allows an efficient and
accurate topological analysis of regions of interest (ROIs) by using a four-level
architecture. By topological analysis, we mean not only the computation of Euler
characteristic, genus or Betti numbers, but also advanced computational algebraic
topological information derived from homological classification of cycles. An initial
HSF representation can be modified to obtain a different one, in which ROIs are
almost isolated and ready to be topologically analyzed. The HSF framework is
susceptible of being parallelized and generalized to higher dimensions.

http://dx.doi.org/10.1007/s10472-012-9297-7