Review on Multimodal Biometric Recognition System Using Machine Learning

Authors

  • Dipali B. Jadhav Department of Computer Science and Information Technology, Dr. Babasaheb Ambedkar Marathwada University, India https://orcid.org/0009-0005-1959-1976
  • Gaju S. Chavan Department of Computer Science and Information Technology, Dr. Babasaheb Ambedkar Marathwada University, India https://orcid.org/0009-0004-1849-2338
  • Vandana C. Bagal Karmaveer Kakasaheb Wagh Institute of Engineering Education and Research, India https://orcid.org/0000-0001-7341-3912
  • Ramesh R. Manza Department of Computer Science and Information Technology, Dr. Babasaheb Ambedkar Marathwada University, India https://orcid.org/0000-0002-4510-9224

DOI:

https://doi.org/10.47852/bonviewAIA3202593

Keywords:

biometrics, physical, behavioral, source, unimodal, multimodal

Abstract

Biometrics character is the science and innovation of examining organic data of human body for developing frameworks security by giving precise and dependable examples to individual verification and ID and its answers are for the most part utilized in Line, ATM machine, Cell phone, legislatures, enterprises, and so on. Single traits of biological source in biometric system is called unimodal biometric. The unimodal biometric framework is great however they frequently experience the ill effects of certain issues when they face with uproarious information like confined levels of opportunity, intra-class varieties, parody assaults, and non-all-inclusiveness. A few of these issues can be tackled by utilizing multimodal biometric frameworks that consolidate at least two biometric modalities. We have referred papers related multimodal biometrics face, iris, fingerprint, palmprint, hand geometry, ear, voice and signature.This article, we covered different approaches of face and palmprint for human authentication.

 

Received: 23 December 2022 | Revised: 30 June 2023 | Accepted: 7 July 2023

 

Conflicts of Interest

The authors declare that they have no conflicts of interest to this work.

 

Data Availability Statement

Data available on request from the corresponding author upon reasonable request.

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Published

2023-07-14

Issue

Section

Online First Articles

How to Cite

Jadhav, D., Chavan, G. ., Bagal, V. ., & Manza, R. . (2023). Review on Multimodal Biometric Recognition System Using Machine Learning. Artificial Intelligence and Applications. https://doi.org/10.47852/bonviewAIA3202593