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Fractal Topological Analysis for 2D Binary Digital Images

Authors

BLANCO TREJO, SERGIO, Aleman-Morillo, C. , Diaz-del-Rio, F. , Real, P.

External publication

No

Means

Math. Comput. Sci.

Scope

Article

Nature

Científica

JCR Quartile

SJR Quartile

SJR Impact

0.322

Publication date

01/06/2019

ISI

000474596200003

Abstract

Fractal dimension is a powerful tool employed as a measurement of geometric aspects. In this work we propose a method of topological fractal analysis for 2D binary digital images by using a graph-based topological model of them, called Homological Spanning Forest (HSF, for short). Defined at interpixel level, this set of two trees allows to topologically describe the (black and white) connected component distribution within the image with regards to the relationship "to be surrounded by". This distribution is condensed into a rooted tree, such that its nodes are connected components determined by some special sub-trees of the previous HSF and the levels of the tree specify the degree of nesting of each connected component. We ask for topological auto-similarity by comparing this topological description of the whole image with a regular rooted tree pattern. Such an analysis can be used to directly quantify some characteristics of biomedical images (e.g. cells samples or clinical images) that are not so noticeable when using geometrical approaches.

Keywords

Digital image; Region-adjacency tree; Fractal topology; Homological spanning forest

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