Authors: Lifang Tian; Huijuan Xu; Xin Zheng
Addresses: School of Information Engineering, Huanghuai University, Zhu Madian 463000, China ' School of Information Engineering, Huanghuai University, Zhu Madian 463000, China ' School of Information Engineering, Huanghuai University, Zhu Madian 463000, China
Abstract: In order to overcome the problem of poor image matching performance of the image recognition method, a method of fingerprint image recognition based on convolution neural network is proposed. In this method, the defaced fingerprint image is pre-processed by smoothing, convergence, equalisation, background foreground segmentation and distortion correction, and the feature points of the defaced fingerprint image are extracted by combining the neighbourhood judgment method, and the information pseudo feature points are removed by fusing the feature points, the centre points are extracted from the feature points of the defaced fingerprint image, and the centre block image is identified by convolution neural network, so as to realise the defaced fingerprint image distinguish. The experimental results show that the performance of restoration and reconstruction is improved. The rejection rate (FRR) is 3.75%, the false recognition rate (FAR) is 1.25%, and the correct recognition rate (CR) is 99.25%.
Keywords: convolution neural network; defaced fingerprint; image recognition; neighbourhood determination.
International Journal of Biometrics, 2021 Vol.13 No.1, pp.64 - 79
Received: 01 Feb 2020
Accepted: 26 Mar 2020
Published online: 05 Jan 2021 *