SynCoLFinGer: Synthetic Contactless Fingerprint Generator
This addresses the need for synthetic data in contactless fingerprint recognition, which is incremental as it builds on existing synthetic fingerprint generation methods.
The authors tackled the problem of generating synthetic contactless fingerprint images by modeling capturing, subject, and environmental components applied to synthetic ridge patterns, resulting in a method that produces samples of various quality levels and resembles real fingerprints, as confirmed by biometric quality and utility evaluations.
We present the first method for synthetic generation of contactless fingerprint images, referred to as SynCoLFinGer. To this end, the constituent components of contactless fingerprint images regarding capturing, subject characteristics, and environmental influences are modeled and applied to a synthetically generated ridge pattern using the SFinGe algorithm. The proposed method is able to generate different synthetic samples corresponding to a single finger and it can be parameterized to generate contactless fingerprint images of various quality levels. The resemblance of the synthetically generated contactless fingerprints to real fingerprints is confirmed by evaluating biometric sample quality using an adapted NFIQ 2.0 algorithm and biometric utility using a state-of-the-art contactless fingerprint recognition system.