Convolutional Neural Networks in Application to Segmentation of Fingerprint Images

Abstract

Segmentation of fingerprint images is one of the most important problems concerned with automatic biometric identification system. 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 convolutional 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, 2004). The experimental results showed a high quality of segmentation.