General fuzzy difference operator and its application in edge detector
Year: 2025
Type: article
Abstract: This paper gives a more general definition of fuzzy difference operator by relaxing existing constraints, enabling a broader range of operator constructions. The characteristics and attributes of general fuzzy difference operator are thoroughly examined. Then, these novel constructions of general fuzzy difference operator are applied as fuzzy morphological gradient operators in edge detection. Experiments and analyses compare the proposed edge detection algorithm's performance with alternative methods, evaluating various configurations (t-norms, implications, and general fuzzy difference operators). The main findings of this study are: (1) By relaxing the condition, the generalized fuzzy difference operator can be constructed using various t-norms, implications, and fuzzy difference operators, offering greater flexibility in edge detector. (2) The experimental results show that novel fuzzy difference operators applied as fuzzy morphological gradient operators for edge detection in image processing perform better than those existing.
Authors: Zhi Yu Zhang, Bo Wen Fang
Institution: Wuhan University of Technology
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $3,050
Awards: G1059425080, G3978146462
OpenAlex ID: W4410030211
