A novel parametric intuitionistic fuzzy entropy measure with applications to image edge detection
Keywords:
Edge detection, Image processing, Rényi entropy, Intuitionistic fuzzy sets, Generalized fuzzy entropyAbstract
In digital image processing, edge detection is a fundamental operation used to identify intensity discontinuities in an image. In this paper, we propose a novel one-parameter generalization of an entropy measure for intuitionistic fuzzy sets (IFSs). IFSs provide additional flexibility by incorporating membership, non-membership, and hesitation information. A proof of validity is given for the proposed measure, together with numerical and graphical demonstrations. The entropy measure is applied to generate an edge map in which pixels exhibiting higher uncertainty are marked as image edges. Experimental results for standard benchmark images and real photographic images demonstrate superior edge localization and improved quantitative performance compared with existing fuzzy-entropy-based techniques.
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Copyright (c) 2026 Vaishali Manish Joshi, Javid Gani Dar (Author)

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