Efficient Fingerprint Database Organization for Optimized Recognition

A popular biometric identification method, renowned for its dependability and individuality in personal identification, is fingerprint recognition. This article presents an efficient fingerprint identification system that significantly reduces processing times for 100,000 fingerprints from 8 minutes to less than 5 seconds by utilizing multithreading, ANSI 378 templates, and Source AFIS. The system overcomes the time-consuming image-to-template conversion procedure and increases overall storage efficiency by utilizing parallel processing and preformatted templates (ANSI/ISO). The fingerprint matching system incorporates Directional Field, CNN models for identifying fingerprint types, and Finger Code methods to classify fingerprints, improving precision and efficiency.

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Publication Details

Published
2025-03-05
DOI
https://doi.org/10.1109/esci63694.2025.10988054
Primary Topic
Biometric Identification and Security
Type
article
Field-Weighted Citation Impact
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article

Efficient Fingerprint Database Organization for Optimized Recognition

D. Ajitha, A. Koshy, Jeffrey Jeeva Dhas, Nishit Dua
Biometric Identification and Security
article

Efficient Fingerprint Database Organization for Optimized Recognition

D. Ajitha, A. Koshy, Jeffrey Jeeva Dhas, Nishit Dua
article en

Abstract

A popular biometric identification method, renowned for its dependability and individuality in personal identification, is fingerprint recognition. This article presents an efficient fingerprint identification system that significantly reduces processing times for 100,000 fingerprints from 8 minutes to less than 5 seconds by utilizing multithreading, ANSI 378 templates, and Source AFIS. The system overcomes the time-consuming image-to-template conversion procedure and increases overall storage efficiency by utilizing parallel processing and preformatted templates (ANSI/ISO). The fingerprint matching system incorporates Directional Field, CNN models for identifying fingerprint types, and Finger Code methods to classify fingerprints, improving precision and efficiency.

Vellore Institute of Technology University (IN)
Openalex Percentile: Top 89%
Biometric Identification and Security
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