A Fingerprint Detection Method by Fingerprint Ridge Orientation Check
Kim JuSong, Ri IlYong

TL;DR
This paper proposes a new fingerprint detection algorithm that enhances fingerprint recognition systems, leveraging advancements in neural networks to improve accuracy and reliability.
Contribution
It introduces a novel fingerprint detection method based on ridge orientation checks, integrating deep learning techniques to boost recognition performance.
Findings
Improved fingerprint detection accuracy
Enhanced robustness against false positives
Effective integration with neural network-based recognition systems
Abstract
Fingerprints are popular among the biometric based systems due to ease of acquisition, uniqueness and availability. Nowadays it is used in smart phone security, digital payment and digital locker. Fingerprint recognition technology has been studied for a long time, and its recognition rate has recently risen to a high level. In particular, with the introduction of Deep Neural Network technologies, the recognition rate that could not be reached before was reached. In this paper, we propose a fingerprint detection algorithm used in a fingerprint recognition system.
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Taxonomy
TopicsBiometric Identification and Security
