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Fingerprint Recognition System based on Big Data and Multi-feature Fusion by Yang, Mikai is a scholarly article available to read on EtoBox.

What is Fingerprint Recognition System based on Big Data and Multi-feature Fusion about?

This paper proposes a fingerprint recognition algorithm, which is based on deep learning and multi-feature fusion, is able to solve the shortcomings of traditional fingerprint recognition that purely relies on minutiae features for recognition, especially in the case of partially incomplete fingerprints or small-area fingerprints. For identification, while the user inserts a fingerprint in the terminal, the system will transmit raw data to the deep learning engine of the cloud in an anonymous and encrypted manner, which can quickly collect a large amount of fingerprint data in an aligned manner. Based on these data, parameters of the deep-learning model are adjusted incrementally, pursuing optimal accuracy of the system. Meanwhile, SaaS services are provided to other applications for fingerprint recognition.

Author

Yang, Mikai

Publisher

IEEE

Published

2020

Language

EN