Unconstrained Hand Dorsal Veins Image Database and Recognition System  

作　　者：Mustafa M.Al Rifaee Mohammad M.Abdallah Mosa I.Salah Ayman M.Abdalla 

机构地区：[1]Faculty of Science and Information Technology,Al-Zaytoonah University of Jordan,Amman,11733,Jordan [2]Faculty of Architecture and Design,Al-Zaytoonah University of Jordan,Amman,11733,Jordan

出　　处：《Computers, Materials & Continua》2022年第12期5063-5073,共11页计算机、材料和连续体（英文）

基　　金：This research was funded by Al-Zaytoonah University of Jordan Grant Number(2020-2019/12/11).

摘　　要：Hand veins can be used effectively in biometric recognition since they are internal organs that,in contrast to fingerprints,are robust under external environment effects such as dirt and paper cuts.Moreover,they form a complex rich shape that is unique,even in identical twins,and allows a high degree of freedom.However,most currently employed hand-based biometric systems rely on hand-touch devices to capture images with the desired quality.Since the start of the COVID-19 pandemic,most handbased biometric systems have become undesirable due to their possible impact on the spread of the pandemic.Consequently,new contactless hand-based biometric recognition systems and databases are desired to keep up with the rising hygiene awareness.One contribution of this research is the creation of a database for hand dorsal veins images obtained contact-free with a variation in capturing distance and rotation angle.This database consists of 1548 images collected from 86 participants whose ages ranged from 19 to 84 years.For the other research contribution,a novel geometrical feature extraction method has been developed based on the Curvelet Transform.This method is useful for extracting robust rotation invariance features from vein images.The database attributes and the veins recognition results are analyzed to demonstrate their efficacy.

关 键 词：Biometric recognition contactless hand biometrics veins recognition Curvelet transform image segmentation feature extraction 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]