A Real Time of an Automatic Finger Vein Recognition System

Resumo

Finger vein recognition biometric system is one of the most current and accurate biometric technologies. Yet, early implementation of this technology is not widely used in real-time applications. In this work, a finger vein-embedded system based on Rasberry-Pi has been presented. In our process, we use four structural directional elements for smoothing finger veins ROIs. A Top-Hat and Bottom-Hat kernel filters are used to enhance the contrast quality of images. For feature extraction step, we used two approaches for the synthesis of attributes including the geometric and texture representations of venous prints. The first one is a Local Directional Code (LDC) descriptor that characterizes texture and directional information of finger vein print. The Improved Gaussian Matched Filter (IMPGMF) is used to extract the finger vein map that characterised geometric venous information. The proposed vision system presents an Error Equal Rate (EER) lower to 0.02 and Identification Rate (IR) higher to 98.99. Moreover, experimental results show that the designed system is fast enough to run the decision of finger vein verification. Performance results show the efficiency and robustness of our system.