Fuzzy Logic Based Edge Detection Methods: A Systematic Literature Review

Miquéias Silva, Gracaliz Dimuro, Eduardo Nunes Borges, Giancarlo Lucca, Cedric Marco-Detchart

2023

Abstract

Edge detection, or the detection of the maximum limit between two regions with different properties, is one of the classic problems in the area of computer vision. The uncertainty associated with the nature of this detection, such as the characteristic fuzzy transition zone resulting from the image discretization processes, or even noise and illumination variations, justifies an approach based on fuzzy logic theory. In order to understand the state of the art in edge detection techniques using fuzzy logic-based methods, this work proposes a systematic review considering two bibliographic sources of scientific literature, Scopus and Web Of Science. In total, 34 works were selected through a systematic literature review, and their methods were summarized and reported in this research. From this analysis, it could be concluded that, in recent years, fuzzy logic has been employed in hybrid methods in order to improve the performance of existing techniques or reduce computational complexity. Studies with interval fuzzy logic of higher order have been employed for its greater flexibility in dealing with the uncertainty associated with the edge detection task.

Paper Citation

in Harvard Style

Silva M., Dimuro G., Nunes Borges E., Lucca G. and Marco-Detchart C. (2023). Fuzzy Logic Based Edge Detection Methods: A Systematic Literature Review. In Proceedings of the 25th International Conference on Enterprise Information Systems - Volume 1: ICEIS, ISBN 978-989-758-648-4, SciTePress, pages 385-394. DOI: 10.5220/0011853700003467

in Bibtex Style

@conference{iceis23,
author={Miquéias Silva and Gracaliz Dimuro and Eduardo Nunes Borges and Giancarlo Lucca and Cedric Marco-Detchart},
title={Fuzzy Logic Based Edge Detection Methods: A Systematic Literature Review},
booktitle={Proceedings of the 25th International Conference on Enterprise Information Systems - Volume 1: ICEIS,},
year={2023},
pages={385-394},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011853700003467},
isbn={978-989-758-648-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 25th International Conference on Enterprise Information Systems - Volume 1: ICEIS,
TI - Fuzzy Logic Based Edge Detection Methods: A Systematic Literature Review
SN - 978-989-758-648-4
AU - Silva M.
AU - Dimuro G.
AU - Nunes Borges E.
AU - Lucca G.
AU - Marco-Detchart C.
PY - 2023
SP - 385
EP - 394
DO - 10.5220/0011853700003467
PB - SciTePress