Mathematics for multi-biometrics person recognition systems - Herbadji, Abderrahmane;Guermat, Noubeil;Ziet, Lahcene
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Biometrics is a scientific technology to recognize a person using their physical, behavior or chemical attributes. A system that uses asingle source of biometric information (e.g., single fingerprint) to recognize people is known as unimodal system. Whereas, the system that consolidates data from multiple biometric sources of information (e.g., face and fingerprint) is called multibiometrics system. that can alleviate the error rates and some inherent weaknesses of uni-biometrics.In this work, a novel scheme for score-level fusion based on weighted quasi-arithmetic mean (WQAM) has been…mehr

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Produktbeschreibung
Biometrics is a scientific technology to recognize a person using their physical, behavior or chemical attributes. A system that uses asingle source of biometric information (e.g., single fingerprint) to recognize people is known as unimodal system. Whereas, the system that consolidates data from multiple biometric sources of information (e.g., face and fingerprint) is called multibiometrics system. that can alleviate the error rates and some inherent weaknesses of uni-biometrics.In this work, a novel scheme for score-level fusion based on weighted quasi-arithmetic mean (WQAM) has been proposed. Specifically, WQAMs are estimated via different trigonometric functions. The proposed fusion scheme encompasses properties of both weighted mean and quasi-arithmetic mean. Experimental results on three publicly available data sets for multi-modal,multi-unit and multi-algorithm systems show that presented WQAM fusion algorithm outperforms the previously previously proposed score fusion rules.In addition, a palm and wrist vein-based multi biometric system based on triangular norms is proposed.
Autorenporträt
The author holds Bachelor¿s in Electronics and Master¿s in Electronics of Embedded Systems from Setif-1 University, Algeria, in 2015 and 2017, respectively, and the Ph.D. degree in Electronics in 2021 from University of M¿Sila, Algeria. His research interests include mathematics, image processing and deep learning with applications to biometrics.