Neuro-inspired edge feature fusion using Choquet integrals

Marco Detchart, Cedric; Lucca, Giancarlo; López Molina, Carlos; Miguel Turullols, Laura de; Pereira Dimuro, Graçaliz; Bustince Sola, Humberto

Publication:
Neuro-inspired edge feature fusion using Choquet integrals

dc.contributor.author	Marco Detchart, Cedric
dc.contributor.author	Lucca, Giancarlo
dc.contributor.author	López Molina, Carlos
dc.contributor.author	Miguel Turullols, Laura de
dc.contributor.author	Pereira Dimuro, Graçaliz
dc.contributor.author	Bustince Sola, Humberto
dc.contributor.department	Estadística, Informática y Matemáticas	es_ES
dc.contributor.department	Estatistika, Informatika eta Matematika	eu
dc.contributor.funder	Universidad Pública de Navarra / Nafarroako Unibertsitate Publikoa	es
dc.date.accessioned	2022-04-12T06:27:07Z
dc.date.available	2022-04-12T06:27:07Z
dc.date.issued	2021
dc.description.abstract	It is known that the human visual system performs a hierarchical information process in which early vision cues (or primitives) are fused in the visual cortex to compose complex shapes and descriptors. While different aspects of the process have been extensively studied, such as lens adaptation or feature detection, some other aspects, such as feature fusion, have been mostly left aside. In this work, we elaborate on the fusion of early vision primitives using generalizations of the Choquet integral, and novel aggregation operators that have been extensively studied in recent years. We propose to use generalizations of the Choquet integral to sensibly fuse elementary edge cues, in an attempt to model the behaviour of neurons in the early visual cortex. Our proposal leads to a fully-framed edge detection algorithm whose performance is put to the test in state-of-the-art edge detection datasets.	en
dc.description.sponsorship	The authors gratefully acknowledge the financial support of the Spanish Ministry of Science and Technology (project PID2019-108392GB-I00 (AEI/10.13039/501100011033), the Research Services of Universidad Pública de Navarra, CNPq (307781/2016-0, 301618/2019-4), FAPERGS (19/2551-0001660) and PNPD/CAPES (464880/2019-00).	en
dc.format.extent	18 p.
dc.format.mimetype	application/pdf	en
dc.identifier.doi	10.1016/j.ins.2021.10.016
dc.identifier.issn	0020-0255
dc.identifier.uri	https://academica-e.unavarra.es/handle/2454/42714
dc.language.iso	eng	en
dc.publisher	Elsevier	en
dc.relation.ispartof	Information Sciences, 581, p. 740-754, 2021	en
dc.relation.projectID	info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2019-108392GB-I00/ES/	en
dc.relation.publisherversion	https://doi.org/10.1016/j.ins.2021.10.016
dc.rights	© 2021 The Authors. Creative Commons Attribution 4.0 International	en
dc.rights.accessRights	info:eu-repo/semantics/openAccess	en
dc.rights.accessRights	Acceso abierto / Sarbide irekia	es
dc.rights.uri	http://creativecommons.org/licenses/by/4.0/
dc.subject	CF-integral	en
dc.subject	Choquet integral	en
dc.subject	Edge detection	en
dc.subject	Feature extraction	en
dc.subject	Image processing	en
dc.subject	Re-aggregation functions	en
dc.title	Neuro-inspired edge feature fusion using Choquet integrals	en
dc.type	Artículo / Artikulua	es
dc.type	info:eu-repo/semantics/article	en
dc.type.version	info:eu-repo/semantics/publishedVersion	en
dc.type.version	Versión publicada / Argitaratu den bertsioa	es
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