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

Revista:
Pattern Recognition Letters

ISSN: 0167-8655

Año de publicación: 2016

Tipo: Artículo

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

Otras publicaciones en: Pattern Recognition Letters

Resumen

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.