  Local feature descriptors exhibit great superiority in finger vein
recognition due to their stability and robustness against local changes in
images. However, most of these are methods use general-purpose descriptors that
do not consider finger vein-specific features. In this work, we propose a
finger vein-specific local feature descriptors based physiological
characteristic of finger vein patterns, i.e., histogram of oriented
physiological Gabor responses (HOPGR), for finger vein recognition. First,
prior of directional characteristic of finger vein patterns is obtained in an
unsupervised manner. Then the physiological Gabor filter banks are set up based
on the prior information to extract the physiological responses and
orientation. Finally, to make feature has robustness against local changes in
images, histogram is generated as output by dividing the image into
non-overlapping cells and overlapping blocks. Extensive experimental results on
several databases clearly demonstrate that the proposed method outperforms most
current state-of-the-art finger vein recognition methods.
