A Study of New Indexing Techniques for Multimodal Identification Using Iris, Fingerprint, and Face Biometrics

This paper explores innovative indexing techniques for multimodal biometric identification systems, focusing on iris, fingerprint, and facial recognition technologies. With the proliferation of digital identity verification needs, traditional single-modal biometric systems often fall short in terms of accuracy, speed, and security. Multimodal biometric systems, which integrate multiple biological characteristics, are becoming crucial for enhancing identification performance. This study aims to present a comprehensive analysis of new indexing methods that can significantly improve the efficiency, accuracy, and security of multimodal biometric identification systems.

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Publication Details

Journal
Journal of Advances in Science and Technology
Published
2024-09-02
DOI
https://doi.org/10.29070/6eqjyg33
Primary Topic
Biometric Identification and Security
Type
article
Field-Weighted Citation Impact
0.00
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article

A Study of New Indexing Techniques for Multimodal Identification Using Iris, Fingerprint, and Face Biometrics

Gaurav Khandelwal, Payal Jain
Journal of Advances in Science and Technology
Biometric Identification and Security
article

A Study of New Indexing Techniques for Multimodal Identification Using Iris, Fingerprint, and Face Biometrics

Gaurav Khandelwal, Payal Jain
article en

Abstract

This paper explores innovative indexing techniques for multimodal biometric identification systems, focusing on iris, fingerprint, and facial recognition technologies. With the proliferation of digital identity verification needs, traditional single-modal biometric systems often fall short in terms of accuracy, speed, and security. Multimodal biometric systems, which integrate multiple biological characteristics, are becoming crucial for enhancing identification performance. This study aims to present a comprehensive analysis of new indexing methods that can significantly improve the efficiency, accuracy, and security of multimodal biometric identification systems.

Journal of Advances in Science and TechnologyVol. 20(2)
University of Rajasthan (IN)
Openalex Percentile: Top 85%
Biometric Identification and Security
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