New Feature-level Algorithm for a Face-fingerprint Integral Multi-biometrics Identification System

Authors

  • Bayan Omar Department of Information Technology, College of Science and Technology, University of Human Development, Kurdistan Region, Iraq
  • Hamsa D. Majeed Department of Information Technology, College of Science and Technology, University of Human Development, Kurdistan Region, Iraq
  • Siti Zaiton Mohd Hashim Department of Data Science, Universiti Malaysia Kelantan (UMK), Taman Bendahara, 16100 Pengkalan Chepa, Kelantan
  • Muzhir Al-Ani Department of Information Technology, College of Science and Technology, University of Human Development, Kurdistan Region, Iraq

DOI:

https://doi.org/10.21928/uhdjst.v6n1y2022.pp12-20

Keywords:

Multi-model Biometric, Dis-Eigen algorithm, Identification, Aspect United Moment Invariant

Abstract

This article delves into the power of multi-biometric fusion for individual identification. a new feature-level algorithm is proposed that is the Dis-Eigen algorithm. Here, a feature-fusion framework is proposed for attaining better accuracy when identifying individuals for multiple biometrics. The framework, therefore, underpins the new multi-biometric system as it guides multi-biometric fusion applications at the feature phase for identifying individuals. In this regard, the Face-fingerprints of 20 individuals represented by 160 images were used in this framework . Experimental resultants of the proposed approach show 93.70 % identification rate with feature-level fusion multi-biometric individual identification.

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Published

2022-02-11

Issue

Section

Articles