Research on fingerprint image recognition based on convolution neural network Online publication date: Tue, 05-Jan-2021
by Lifang Tian; Huijuan Xu; Xin Zheng
International Journal of Biometrics (IJBM), Vol. 13, No. 1, 2021
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%.
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Biometrics (IJBM):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email subs@inderscience.com
Our Blog 
Follow us on Twitter 
Visit us on Facebook