Zigzag persistence for image processing: New software and applications
Resumen: Topological image analysis is a powerful tool for understanding the structure and topology of images, being persistent homology one of its most popular methods. However, persistent homology requires a chain of inclusions of topological spaces, which can be challenging for digital images. In this article, we explore the use of zigzag persistence, a recent variant of traditional persistence, for digital image processing. To this end, new algorithms are developed to build a simplicial complex associated to a digital image and to compute the relationships between homology classes of a sequence of binary images via zigzag persistence. Additionally, we provide a simple software to use them. We demonstrate its effectiveness by applying it to a real-world problem of analyzing honey bee sperm videos.
Idioma: Inglés
DOI: 10.1016/j.patrec.2024.06.010
Año: 2024
Publicado en: PATTERN RECOGNITION LETTERS 184 (2024), 111-118
ISSN: 0167-8655

Financiación: info:eu-repo/grantAgreement/ES/AEI/PID2020-112673RB-I00
Financiación: info:eu-repo/grantAgreement/ES/AEI/PID2020-116641GB-I00
Financiación: info:eu-repo/grantAgreement/ES/DGA-FSE/A07_23R
Tipo y forma: Article (Published version)
Área (Departamento): Área Producción Animal (Dpto. Produc.Animal Cienc.Ali.)

Creative Commons You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use. You may not use the material for commercial purposes.


Exportado de SIDERAL (2024-07-19-18:29:16)


Visitas y descargas

Este artículo se encuentra en las siguientes colecciones:
Articles



 Record created 2024-07-19, last modified 2024-07-19


Versión publicada:
 PDF
Rate this document:

Rate this document:
1
2
3
 
(Not yet reviewed)