Fingerprint recognition using standardized fingerprint model

TL;DR

This paper introduces a standardized fingerprint model that synthesizes fingerprint templates to improve recognition accuracy, especially in poor quality images, by transforming, adjusting, and noise-reducing fingerprint data before matching.

Contribution

The paper proposes a novel standardized fingerprint model that enhances fingerprint recognition by synthesizing templates and reducing noise, improving accuracy in challenging image conditions.

Findings

Effective synthesis of fingerprint templates demonstrated.

Improved recognition accuracy on FVC2004 database.

Model reduces noise and aligns templates for better matching.

Abstract

Fingerprint recognition is one of most popular and accuracy Biometric technologies. Nowadays, it is used in many real applications. However, recognizing fingerprints in poor quality images is still a very complex problem. In recent years, many algorithms, models...are given to improve the accuracy of recognition system. This paper discusses on the standardized fingerprint model which is used to synthesize the template of fingerprints. In this model, after pre-processing step, we find the transformation between templates, adjust parameters, synthesize fingerprint, and reduce noises. Then, we use the final fingerprint to match with others in FVC2004 fingerprint database (DB4) to show the capability of the model.