Title: Research on fingerprint feature recognition of access control based on deep learning
Authors: Xiaochang Lv; Li Ding; Guohua Zhang
Addresses: College of Electrical and Information Engineering, Northeast Petroleum University, Daqing 163318, China ' Library, Northeast Petroleum University, Daqing 163318, China ' Big Data and Computer Science, Northeast Petroleum University, Daqing 163318, China
Abstract: In order to overcome the problems of large error and long time-consuming in traditional feature recognition methods, this paper proposes a new fingerprint feature recognition method based on deep learning. Firstly, fingerprint identity database is established, and the access control fingerprint image is collected by the modified hardware equipment, and the image pre-processing is realised from two aspects: image screening and morphological processing. In this framework, the fingerprint direction field in the fingerprint image is screened through multiple iterations. The feature points in the fingerprint image of access control are extracted, and the similarity between the image and the information base is calculated. The experimental results show that compared with the traditional recognition method, the recognition speed of the proposed method is improved by about 6.6 seconds on the premise of ensuring the accuracy of recognition.
Keywords: deep learning; access control fingerprint; fingerprint feature; feature recognition.
International Journal of Biometrics, 2021 Vol.13 No.1, pp.80 - 95
Received: 01 Feb 2020
Accepted: 26 Mar 2020
Published online: 05 Jan 2021 *