International Research Journal of Innovations in Engineering and Technology - IRJIET International Open Access, Monthly, Peer Reviewed, Reputed Journal ISSN (online): 2581-3048

Impact Factor (2025): 6.9

DOI Prefix: 10.47001/IRJIET

Biometric Recognition System Based on Feature Fusion: Face and Palm Print

Abstract

This study introduces an advanced biometric recognition system that seamlessly integrates facial and palm print modalities, showcasing outstanding performance across diverse datasets. The facial recognition dataset exhibits remarkable training, validation, and test accuracies at 98.98%, 98.99%, and 99%, respectively. Precision, recall, and F1-score metrics consistently reach 99%, underlining the system's robust and reliable performance in facial identification. Similarly, the palm print dataset demonstrates impressive results, with training, validation, and test accuracies at 98.90%, 99%, and 99%, respectively. Precision, recall, and F1-scores maintain a high level of 99%, emphasizing the system's effectiveness in palm print recognition. The combined "Face and Palm" dataset further highlights the system's exceptional capabilities, achieving perfect scores of 100% in training, validation, and test accuracies, as well as precision, recall, and F1-score. This underscores the system's versatility and proficiency in simultaneously recognizing facial and palm features. The innovative fusion of facial and palm print modalities in this biometric recognition system yields impressive and consistent results across multiple datasets. The system's high accuracy and precision, coupled with its adaptability to various scenarios, position it as a valuable advancement in biometric technology.

Country : Iraq

1 Abeer A. Mohamad Alshiha

  1. Remote Sensing Center, Mosul University, Mosul-Iraq

IRJIET, Volume 7, Issue 12, December 2023 pp. 281-288

doi.org/10.47001/IRJIET/2023.712038

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