CNN-based High-Resolution Fingerprint Image Enhancement for Pore Detection and Matching

摘要

Pore is widely used because of its strong security and usefulness for live fingerprint detection and recognition. There are considerable pores in a high-resolution fingerprint image that can be used for fingerprint recognition. However, the quality of fingerprint has become one of the bottlenecks in the method of pore detection and matching currently. In order to improve the accuracy and stability of the existing pore detection and matching methods, this paper proposes a fingerprint enhancement technique based on neural network. The residual structure is used to learn the local features of the fingerprint to reconstruct the original image. Experimental results indicate the approach can improve the precision of the existing pore extraction and matching methods significantly.