Authors:
Miquéias Silva
1
;
Gracaliz Dimuro
1
;
Eduardo Nunes Borges
1
;
Giancarlo Lucca
1
and
Cedric Marco-Detchart
2
Affiliations:
1
Center of Computational Sciences, Federal University of Rio Grande, Itália avenue, Rio Grande - RS, Brazil
;
2
Universitat Politècnica de València, Valencia, Comunitat Valenciana, Spain
Keyword(s):
Edge Detection, Fuzzy Methods, Systematic Literature Review.
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 complexi
ty. 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.
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