Finger vein recognition via local multilayer ternary pattern

Abstract

We propose a novel method for finger vein recognition in this paper. We use even symmetrical Gabor filters to smooth images and remove noise, then Contrast Limited Adaptive Histogram Equalization (CLAHE) is utilized for image enhancement. Finger Vein is extracted via Maximum Curvature (MC), and after thinning by morphological filter, we use Local multilayer Ternary Pattern (LmTP) descriptor proposed in this paper to extract finger vein features. We also propose an algorithm to calculating the similarity of LmTP features. Experiment results show the performance of the proposed method is better than other well-known metrics and LmTP is more robust than other local feature descriptors like LBP, LTP and LmBP.