Research Article

Some Matlab Applications of Distance and Similarity Measures for Fuzzy Sets

Authors

Esra Gülle * Department of Mathematics, Faculty of Science and Literature, Afyon Kocatepe University, Afyonkarahisar, Turkey.
Özge Kaya Department of Mathematics, Faculty of Science and Literature, Afyon Kocatepe University, Afyonkarahisar, Turkey.

https://doi.org/10.22105/scfa.v1i1.32

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Abstract

The aim of this study is to compare the similarity ratios between the Sobel, Prewitt, Laplacian, Canny and Robert-Cross edge detection filters, which are frequently used in edge detection, and the fuzzy edge detection filter obtained using fuzzy logic with the help of Hamming, Euclidean and Minkowski distance measures in Matlab.

Keywords

Fuzzy set Fuzzy distance measures Fuzzy similarity measures Matlab‎

References (13)

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[2] Atanassov, K.T. (1999). Intuitionistic fuzzy sets. Physica, Heidelberg. https://doi.org/10.1007/978-3-7908-1870-3_1

[3] Goguen, J. A. (1967). L-fuzzy sets. Journal of mathematical analysis and applications, 18(1), 145–174. https://doi.org/10.1016/0022-247X(67)90189-8

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[5] Aborisade, D. O. (2010). Fuzzy logic based digital image edge detection. Global journal of computer science and technology, 10(14), 78–83. https://computerresearch.org/index.php/computer/article/view/657

[6] Kushwaha, N. (2012). Edge detection using fuzzy logic in Matlab. International journal of advanced research in computer science and software engineering, 2(4), 38–40. https://B2n.ir/ps1974

[7] Muhammad Rizky Alditra Utama, K., Umar, R., & Yuhdana, A. (2022). Edge detection comparative analysis using Roberts, Sobel, Prewitt, and Canny methods. Jurnal teknologi dan sistem komputer, 10(2), 67–71. https://doi.org/10.14710/jtsiskom.2021.14209

[8] Xuecheng, L. (1994). Entropy, distance measure and similarity measure of fuzzy sets and their relations. Fuzzy sets and systems, 62(3), 377. https://doi.org/10.1016/0165-0114(94)90124-4

[9] Liu, H. W. (2005). New similarity measures between intuitionistic fuzzy sets and between elements. Mathematical and computer modelling, 42(1–2), 61–70. https://doi.org/10.1016/j.mcm.2005.04.002

[10] Setnes, M., Babuška, R., Kaymak, U., & Van Nauta Lemke, H. R. (1998). Similarity measures in fuzzy rule base simplification. IEEE transactions on systems, man, and cybernetics, part b: Cybernetics, 28(3), 376–386. https://doi.org/10.1109/3477.678632

[11] Omran, S., & Hassaballah, M. (2006). A new class of similarity measures for fuzzy sets. International journal of fuzzy logic and intelligent systems, 6(2), 100–104. https://doi.org/10.5391/IJFIS.2006.6.2.100

[12] Chen, S. M., Yeh, M. S., & Hsiao, P. Y. (1995). A comparison of similarity measures of fuzzy values. Fuzzy sets and systems, 72(1), 79–89. https://doi.org/10.1016/0165-0114(94)00284-E

[13] Beg, I., & Ashraf, S. (2009). Similarity measures for fuzzy sets. Applied and computational mathematics, 8(2), 192–202. https://www.researchgate.net/publication/228744370

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Published 2024-03-11
Issue Vol. 1 No. 1 (2024): Soft Computing Fusion with Applications
Section Articles
Document Type Research Article
Views 781
Downloads 284

Categories

Decision Sciences

How to Cite

Gülle, E. ., & Kaya, Özge . (2024). Some Matlab Applications of Distance and Similarity Measures for Fuzzy Sets. Soft Computing Fusion With Applications , 1(1), 44-49. https://doi.org/10.22105/scfa.v1i1.32

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