Segmentation of fingerprint images using the simplest neural networks

Abstract

Segmentation of fingerprint images is one of the most important problems in automated fingerprint identification system (AFIS). Segmentation is used to separate the area of the fingerprint (foreground) from the background and areas that cannot be recovered. We propose a new algorithm for fingerprint segmentation based on simplest neural networks, binary region labeling technique, and morphological image processing. This approach was tested on public fingerprint dataset provided by Fingerprint Verification Competition (FVC) 2002. The experimental results showed an impressive accuracy was obtained: FAR 2.4%, FRR 1.1% with per-pixel comparison with the reference.