Zigzag persistence for image processing: New software and applications

Divasón, Jose ; Romero, Ana ; Santolaria, Pilar (Universidad de Zaragoza) ; Yániz, Jesús L. (Universidad de Zaragoza)

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

Factor impacto JCR: 3.3 (2024)

Categ. JCR: COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE rank: 93 / 204 = 0.456 (2024) - Q2 - T2

Factor impacto SCIMAGO: 1.005 - Computer Vision and Pattern Recognition (Q1) - Software (Q1) - Signal Processing (Q1) - Artificial Intelligence (Q2)

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: Artículo (Versión definitiva)

Área (Departamento): Área Producción Animal (Dpto. Produc.Animal Cienc.Ali.)