Minutiae feature analysis for infrared hand vein pattern biometrics
Minutiae feature analysis for infrared hand vein pattern biometrics
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DOI：
10.1016/j.patcog.2007.07.012
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发表时间：
2008-03
期刊：
影响因子：
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通讯作者：
Lingyu Wang;G. Leedham;Siu-Yeung Cho
中科院分区：
文献类型：
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作者：
Lingyu Wang;G. Leedham;Siu-Yeung Cho
本文提出了一种新的技术来分析红外静脉模式在手背生物识别的目的。该技术利用从静脉模式中提取的细节特征进行识别，其中包括分叉点和结束点。与指纹类似，这些特征点被用作静脉图案形状的几何表示。红外静脉图案的数据库的分析示出的趋势，对于每个手静脉图案图像，在每个静脉图案图像中平均有13个细节点，包括7个分叉点和6个结束点。提出了改进的Hausdorff距离算法来评估这些细节点的鉴别能力，用于个人验证目的。实验结果表明，该算法在47个不同受试者的数据库上的等错误率（EER）达到0%，表明静脉模式的细节特征可以用于个人身份验证任务。本文还介绍了预处理技术，以获得细节点，以及深入研究其公差的加工误差，如损失的功能和几何位移。
This paper proposes a novel technique to analyze the infrared vein patterns in the back of the hand for biometric purposes. The technique utilizes the minutiae features extracted from the vein patterns for recognition, which include bifurcation points and ending points. Similar to fingerprints, these feature points are used as a geometric representation of the shape of vein patterns. Analysis of a database of infrared vein patterns shows a trend that for each hand vein pattern image, there are, on average, 13 minutiae points in each vein pattern image, including 7 bifurcation and 6 ending points. The modified Hausdorff distance algorithm is proposed to evaluate the discriminating power of these minutiae for person verification purposes. Experimental results show the algorithm reaches 0% of equal error rate (EER) on the database of 47 distinct subjects, which indicates the minutiae features of the vein pattern can be used to perform personal verification tasks. The paper also presents the preprocessing techniques to obtain the minutiae points as well as in-depth study on their tolerance to processing errors, such as loss of features and geometrical displacement.