Effective homology of filtered digital images

  1. Romero, A. 1
  2. Rubio, J. 1
  3. Sergeraert, F. 2
  1. 1 Universidad de La Rioja
    info

    Universidad de La Rioja

    Logroño, España

    ROR https://ror.org/0553yr311

  2. 2 Joseph Fourier University
    info

    Joseph Fourier University

    Grenoble, Francia

    ROR https://ror.org/02aj0kh94

Revue:
Pattern Recognition Letters

ISSN: 0167-8655

Année de publication: 2016

Type: Article

DOI: 10.1016/J.PATREC.2016.01.023 SCOPUS: 2-s2.0-84959214317 WoS: WOS:000386874700004 GOOGLE SCHOLAR

D'autres publications dans: Pattern Recognition Letters

Projets liés

Formalización de las matemáticas: aplicaciones en cálculo simbólico y álgebra computacional. Formalization of mathematics. applications to symbolic computation and computer algebra.

2015/00074/001

Résumé

In this paper, three Computational Topology methods (namely effective homology, persistent homology and discrete vector fields) are mixed together to produce algorithms for homological digital image processing. The algorithms have been implemented as extensions of the Kenzo system and have shown a good performance when applied on some actual images extracted from a public dataset. © 2016 Elsevier B.V.