A GUI-Based Peg-Free Hand Geometry Recognition for Biometric Access Control using Artificial Neural Network

K. Adedeji, Oluwatimilehi A. Esan
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Abstract

Hand geometry has been a widely used biometric authentication because it is generally believed that the human hand has sufficient anatomical features which could be used for personal identification. Many hand geometry systems use pegs, which guide hand placement on the scanner. The system prompts the user to position the hand on the scanner several times and only captures when the current position is satisfied. In such a system, measurements are not very precise and this reduces accuracy during feature extraction. The system also has a higher false acceptance rate. This paper presents a peg-free hand geometry recognition system that does not depend on the orientation of the hand. Several features from test hand images are extracted and stored in the database, which are used to train an artificial neural network (ANN). To facilitate easy usage of the hand geometry verification system (peg-free), a GUI was developed using MATLAB software. The developed system was validated and the overall result shows that the system can be used for biometric verification using hand geometry where the orientation and placement of the hand are not a necessity. The results show that the developed system performed better with a relatively low false acceptance rate and false rejection rate of 0.01% and 0.02% respectively. The system also has a lower mean square error of 8.84×10-5.
基于gui的人工神经网络生物特征门禁免托手几何识别
手的几何形状是一种广泛使用的生物识别方法,因为人们普遍认为人的手具有足够的解剖特征,可以用于个人身份识别。许多手几何系统使用针,它引导手在扫描仪上的位置。系统提示用户将手放在扫描仪上几次,并仅在当前位置满意时进行捕获。在这样的系统中,测量不是很精确,这降低了特征提取的准确性。该系统也有较高的误接受率。提出了一种不依赖手部方向的无支架手部几何识别系统。从测试手图像中提取多个特征并存储在数据库中,用于训练人工神经网络(ANN)。为了方便使用无挂钩手形验证系统,利用MATLAB软件开发了图形用户界面。对所开发的系统进行了验证,总体结果表明,该系统可以使用手的几何形状进行生物特征验证,而手的方向和位置是不必要的。结果表明,所开发的系统具有较低的误接受率和误拒率,分别为0.01%和0.02%。该系统的均方误差也较低,为8.84×10-5。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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