Finger-vein recognition by using spatial feature interdependence matrix weighted by probability and direction

Abstract

The spatial feature interdependence matrix (SFIM) has been proposed for face representation, which encodes feature interdependences between local patches. However, not all patches are equally important for classification purposes. For finger-vein identification, patches that contain vein lines contribute more to classification. Inspired by this, we propose a weighted SFIM based on probability and direction (PDSFIM). Both the probability and direction of vein lines in a patch are integrated into the SFIM. The experimental results demonstrate the superiority of the proposed method after comparison with various state-of-the-art methods.