Multimodal Biometrics for Human Identification using Artificial Intelligence
Boda Aruna1, M Kezia Joseph2
1Boda Aruna, Ph. D Scholar, UCE-Osmania University, Hyderabad (Telangana), India.
2Dr. M Kezia Joseph, Department of Electronics & Communication Engineering, Stanley Engineering College (A), Hyderabad (Telangana), India.
Manuscript received on 09 August 2023 | Revised Manuscript received on 09 November 2023 | Manuscript Accepted on 15 December 2023 | Manuscript published on 30 December 2023 | PP: 1-2 | Volume-12 Issue-1, December 2023 | Retrieval Number: 100.1/ijese.A42781013123 | DOI: 10.35940/ijese.A4278.1212123
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Multimodal biometric systems combine multiple biometric modalities to enhance the accuracy and security of human identification. Instead of relying on a single biometric trait (such as fingerprint or face), these systems use a combination of different biometric characteristics to provide a more robust and reliable identification process. The key idea behind multimodal biometrics is that the fusion of diverse biometric data can overcome the limitations of individual modalities, resulting in higher accuracy and lower error rates.
Keywords: Artificial Intelligence, Human Identification
Scope of the Article: Artificial Intelligence