A Real Time of an Automatic Finger Vein Recognition System


如何引用文章

全文:

开放存取 开放存取
受限制的访问 ##reader.subscriptionAccessGranted##
受限制的访问 订阅存取

详细

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.

作者简介

Randa Trabelsi

Sfax Engineering School, Computers Imaging Electronics and Systems Group (CIELS) from Advanced Control and Energy Management Laboratory (CEM-Lab)

编辑信件的主要联系方式.
Email: trabelsiboukhrisranda@live.fr
突尼斯, Sfax

Alima Masmoudi

Sfax Engineering School, Computers Imaging Electronics and Systems Group (CIELS) from Advanced Control and Energy Management Laboratory (CEM-Lab)

Email: trabelsiboukhrisranda@live.fr
突尼斯, Sfax

Dorra Sellami Masmoudi

Sfax Engineering School, Computers Imaging Electronics and Systems Group (CIELS) from Advanced Control and Energy Management Laboratory (CEM-Lab)

Email: trabelsiboukhrisranda@live.fr
突尼斯, Sfax

补充文件

附件文件
动作
1. JATS XML

版权所有 © Pleiades Publishing, Ltd., 2018