Touchless Multiview Fingerprint Acquisition and Mosaicking

Abstract

Touchless fingerprint capture devices have the advantage over traditional touch-based approaches of being hygienic and preventing distortions resulting from the contact of fingers. Single-view acquisition systems bring in problems, such as scene difference and a limited effective area. This paper thus presents a touchless multiview fingerprint capture system that acquires three different views of fingerprint images at the same time. This device is designed by optimizing parameters regarding the captured fingerprint image quality and device size. A fingerprint mosaicking method is proposed to splice together the captured images of a finger to form a new image with a larger useful print area. Optimization design of our device is demonstrated by introducing our design procedure and comparing with current touchless multiview fingerprint acquisition devices. The efficiency of our device is further proved by comparing recognition accuracy between mosaicked images and touch-based fingerprint images. Experimental results also show that our proposed mosaicking method is more robust to low ridge-valley contrast fingerprint images than available methods. The effectiveness of our mosaicking method is further proved by comparing equal error rates with the mosaicking algorithms evaluated on our established database of 541 fingers.