MonogenicCode: A Novel Fast Feature Coding Algorithm with Applications to Finger-Knuckle-Print Recognition

Lin Zhang, Lei Zhang, David Zhang
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引用次数: 48

Abstract

Biometrics based personal authentication is an effective method for recognizing a person's identity. Recently, it is found that the finger-knuckle-print (FKP), which refers to the inherent skin patterns of the outer surface around the phalangeal joint of one's finger, can serve as a distinctive biometric identifier. In this paper, a novel feature extraction and coding method, namely MonogenicCode, is presented based on the monogenic signal theory, and is applied to FKP recognition. For each image pixel, the associated MonogenicCode is a 3-bits vector obtained by binarizing the monogenic signal at this position, and it can reflect the local phase and orientation information at that position. Experiments conducted on our established FKP database indicate that this new method achieves competitive verification accuracy with state-of-the-art methods, while it needs the least time for feature extraction, making it the best choice for real-time applications.
单基因编码:一种新的快速特征编码算法及其在指关节指纹识别中的应用
基于生物特征的个人身份认证是一种有效的身份识别方法。最近,人们发现手指指关节指纹(FKP)可以作为一种独特的生物识别特征,指的是手指指关节周围外表面固有的皮肤图案。本文基于单基因信号理论,提出了一种新的特征提取和编码方法——MonogenicCode,并将其应用于FKP识别。对于每个图像像素,对应的MonogenicCode是对该位置的单基因信号进行二值化得到的一个3位矢量,它可以反映该位置的局部相位和方向信息。在已建立的FKP数据库上进行的实验表明,该方法具有与现有方法相当的验证精度,且特征提取时间最短,是实时应用的最佳选择。
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