Fuzzy integrals for edge detection
Consultable a partir de
2024-08-21
Fecha
2023Autor
Versión
Acceso embargado / Sarbidea bahitua dago
Tipo
Contribución a congreso / Biltzarrerako ekarpena
Versión
Versión aceptada / Onetsi den bertsioa
Identificador del proyecto
MICINN//PID2021-123673OB-C31
Impacto
|
10.1007/978-3-031-39965-7_28
Resumen
In this work, we compare different families of fuzzy integrals
in the context of feature aggregation for edge detection. We analyze the
behaviour of the Sugeno and Choquet integral and some of its generalizations.
In addition, we study the influence of the fuzzy measure over
the extracted image features. For testing purposes, we follow the Bezdek
Breakdown Structure for edge detection and co ...
[++]
In this work, we compare different families of fuzzy integrals
in the context of feature aggregation for edge detection. We analyze the
behaviour of the Sugeno and Choquet integral and some of its generalizations.
In addition, we study the influence of the fuzzy measure over
the extracted image features. For testing purposes, we follow the Bezdek
Breakdown Structure for edge detection and compare the different fuzzy
integrals with some classical feature aggregation methods in the literature.
The results of these experiments are analyzed and discussed in
detail, providing insights into the strengths and weaknesses of each approach.
The overall conclusion is that the configuration of the fuzzy measure
does have a paramount effect on the results by the Sugeno integral,
but also that satisfactory results can be obtained by sensibly tuning such
parameter. The obtained results provide valuable guidance in choosing
the appropriate family of fuzzy integrals and settings for specific applications.
Overall, the proposed method shows promising results for edge
detection and could be applied to other image-processing tasks. [--]
Materias
Fuzzy integrals,
Choquet integral,
Sugeno integral,
Feature
extraction,
Edge detection.
Editor
Springer
Publicado en
Massanet, S.; Montes, S.; Ruiz-Aguilera, D.; González-Hidalgo, M. (Eds.). Fuzzy logic and technology, and aggregation operators: 13th Conference of the European Society for Fuzzy Logic and Technology, EUSFLAT 2023, and 12th International Summer School on Aggregation Operators, AGOP 2023. Cham: Springer; 2023. p.330-341 978-3-031-39964-0
Departamento
Universidad Pública de Navarra. Departamento de Estadística, Informática y Matemáticas /
Nafarroako Unibertsitate Publikoa. Estatistika, Informatika eta Matematika Saila
Versión del editor
Entidades Financiadoras
This work was partially supported with grant PID2021-123673OB-C31 funded by
MCIN/AEI/ 10.13039/501100011033 and by ”ERDF A way of making Europe”,
Conseller´ıa d’Innovaci´o, Universitats, Ciencia i Societat Digital from Comunitat
Valenciana (APOSTD/2021/227) through the European Social Fund (Investing
In Your Future), grant from the Reseach Services of Universitat Polit`ecnica de
Val`encia (PAID-PD-22), FAPERGS/Brazil (Proc. 19/2551-0001279-9, 19/2551-
0001660) and CNPq/Brazil (301618/2019-4, 305805/2021-5, Edital 07/2022),
Programa de Apoio `a Fixa¸c˜ao de Jovens Doutores no Brasil (23/2551-0000126-
8).