A New Approach to External and Internal Fingerprint Registration With Multisensor Difference Minimization

Abstract

External fingerprints captured by conventional scanners are easily affected by pollution or abrasion. Optical coherence tomography can capture stable internal fingerprints located inside fingertips but with comparable unstable qualities. External and internal fingerprints have advantages and disadvantages that can be used to complement each other. Registration is the premise of the fusion of these fingerprints. Multisensor differences between external and internal fingerprints, including image style differences and deformations, make the registration challenging. This paper presents a new multisensor fingerprint registration method to align external and internal fingerprints finely for the first time. The proposed method includes two stages. First, a cycle generative adversarial network with a structural constraint is designed to unify the image style of multisensor fingerprints. It can improve the similarity of fingerprints while preserve the valley–ridge structures. Then, a two-step registration with fast digital image correlation and outlier rejection is proposed to realize global to local registration. Comparisons have been performed to demonstrate the advantage of the proposed method in registration accuracy and matching performance. Fingerprint fusion results also verify that the registration and fusion of external and internal fingerprints are conducive to supplement fingerprint information.