Description

Abstract

We proposed an end-to-end finger-vein recognition system based on the blanket dimension and

lacunarity implemented on a DSP platform. The proposed system includes a device for capturing

finger-vein images, a method for ROI segmentation, and a novel method combining blanket

dimension features and lacunarity features for recognition. The images from 600 fingers in the

dataset were taken over long time interval (i.e., from summer to winter) by a prototype device we

built. We propose a real-time embedded finger-vein recognition system for authentication on

mobile devices. The system is implemented on a DSP platform and equipped with a novel finger-

vein recognition algorithm. The proposed system takes only about 0.8 seconds to verify one input

finger vein sample and achieves an equal error rate (EER) of 0.07% on a database of 100 subjects.