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Robustness for Authentication of the Human Using Face, Ear, and Gait Multimodal Biometric System

Robustness for Authentication of the Human Using Face, Ear, and Gait Multimodal Biometric System

Law Kumar Singh, Munish Khanna, Shankar Thawkar, Jagadeesh Gopal
Copyright: © 2021 |Volume: 12 |Issue: 1 |Pages: 34
ISSN: 1947-8186|EISSN: 1947-8194|EISBN13: 9781799861508|DOI: 10.4018/IJISMD.2021010103
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MLA

Singh, Law Kumar, et al. "Robustness for Authentication of the Human Using Face, Ear, and Gait Multimodal Biometric System." IJISMD vol.12, no.1 2021: pp.39-72. http://doi.org/10.4018/IJISMD.2021010103

APA

Singh, L. K., Khanna, M., Thawkar, S., & Gopal, J. (2021). Robustness for Authentication of the Human Using Face, Ear, and Gait Multimodal Biometric System. International Journal of Information System Modeling and Design (IJISMD), 12(1), 39-72. http://doi.org/10.4018/IJISMD.2021010103

Chicago

Singh, Law Kumar, et al. "Robustness for Authentication of the Human Using Face, Ear, and Gait Multimodal Biometric System," International Journal of Information System Modeling and Design (IJISMD) 12, no.1: 39-72. http://doi.org/10.4018/IJISMD.2021010103

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Abstract

Biometrics is the science that deals with personal human physiological and behavioral characteristics such as fingerprints, handprints, iris, voice, face recognition, signature recognition, ear recognition, and gait recognition. Recognition using a single trait has several problems and multimodal biometrics system is one of the solutions. In this work, the novel and imperative biometric feature gait is fused with face and ear biometric features for authentication and to overcome problems of the unimodal biometric recognition system. The authors have also applied various normalization methods to sort out the best solution for such a challenge. The feature fusion of the proposed multimodal biometric system has been tested using Min-Max and Z-score techniques. The computed results demonstrate that Z-Score outperforms the Min-Max technique. It is deduced that the Z-score is a promising method that generates a high recognition rate of 95% and a false acceptance rate of 10%.

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