An Analysis of Global and Adaptive Thresholding for Biometric Images Based on Neutrosophic Overset and Underset Approaches
Symmetry, ISSN: 2073-8994, Vol: 15, Issue: 5
2023
- 3Citations
- 4Captures
- 2Mentions
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School of Advanced Sciences Researcher Has Provided New Study Findings on Mathematics (An Analysis of Global and Adaptive Thresholding for Biometric Images Based on Neutrosophic Overset and Underset Approaches)
2023 JUN 06 (NewsRx) -- By a News Reporter-Staff News Editor at Math Daily News -- Fresh data on mathematics are presented in a new
Article Description
The study introduces a new threshold method based on a neutrosophic set. The proposal applies the neutrosophic overset and underset concepts for thresholding the image. The global threshold method and the adaptive threshold method were used as the two types of thresholding methods in this article. Images could be symmetrical or asymmetrical in professional disciplines; the government maintains facial image databases as symmetrical. General-purpose images do not need to be symmetrical. Therefore, it is essential to know how thresholding functions in both scenarios. Since the article focuses on biometric image data, face and fingerprint data were considered for the analysis. The proposal provides six techniques for the global threshold method based on neutrosophic membership, indicating neutrosophic (Formula presented.) overset ((Formula presented.)), neutrosophic (Formula presented.) overset ((Formula presented.)), neutrosophic (Formula presented.) overset ((Formula presented.)), neutrosophic (Formula presented.) underset ((Formula presented.)), neutrosophic (Formula presented.) underset ((Formula presented.)), neutrosophic (Formula presented.) underset ((Formula presented.)); similarly, in this study, the researchers generated six novel approaches for the adaptive method. These techniques involved an investigation using biometric data, such as fingerprints and facial images. The achievement was (Formula presented.) accurate for facial image data and (Formula presented.) accurate for fingerprint data.
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