Ordered directional monotonicity in the construction of edge detectors
Fecha
2021Autor
Versión
Acceso abierto / Sarbide irekia
Tipo
Artículo / Artikulua
Versión
Versión aceptada / Onetsi den bertsioa
Identificador del proyecto
Impacto
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10.1016/j.fss.2020.07.002
Resumen
In this paper we provide a specific construction method of ordered directionally monotone functions. We show that the functions obtained with this construction method can be used to build edge detectors for grayscale images. We compare the results of these detectors to those obtained with some other ones that are widely used in the literature. Finally, we show how a consensus edge detector can be ...
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In this paper we provide a specific construction method of ordered directionally monotone functions. We show that the functions obtained with this construction method can be used to build edge detectors for grayscale images. We compare the results of these detectors to those obtained with some other ones that are widely used in the literature. Finally, we show how a consensus edge detector can be built improving the results obtained both by our proposal and by those in the literature when applied individually. [--]
Materias
Ordered directionally monotone function,
Directional monotonicity,
Edge detection,
Consensus image
Editor
Elsevier
Publicado en
Fuzzy Sets and Systems, Vol. 421, 30 September 2021, Pages 111-132
Departamento
Universidad Pública de Navarra/Nafarroako Unibertsitate Publikoa. Institute of Smart Cities - ISC /
Universidad Pública de Navarra. Departamento de Estadística, Informática y Matemáticas /
Nafarroako Unibertsitate Publikoa. Estatistika, Informatika eta Matematika Saila /
Universidad Pública de Navarra. Departamento de Ingeniería /
Nafarroako Unibertsitate Publikoa. Ingeniaritza Saila
Versión del editor
Entidades Financiadoras
This work was supported by the Slovak Research and Development Agency through grant APVV-18-0052 and the Grant Agency of the Czech Republic, through grant GACR 1806915S, and by the Spanish Government through project PID2019-108392GB-I00 (AEI/FEDER, UE) .