Study of Hand-Dorsa Vein Recognition
Study of Hand-Dorsa Vein Recognition
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DOI：
10.1007/978-3-642-14922-1_61
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发表时间：
2010-08
期刊：
影响因子：
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通讯作者：
Yiding Wang;Kefeng Li;Jiali Cui;L. Shark;M. Varley
中科院分区：
文献类型：
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作者：
Yiding Wang;Kefeng Li;Jiali Cui;L. Shark;M. Varley
提出了一种基于局部分割二值模式（PLBP）的手背静脉识别新方法。该方法采用低成本近红外设备获取的手背静脉图像。经过预处理后，将图像分成子图像。从所有子图像中提取LBP均匀模式特征，并将其组合成标记静脉纹理特征向量。通过计算被测样本和目标样本的特征向量之间的卡方统计量获得的相似性度量来评估该方法。采用积分直方图法、原始LBP法和分区LBP法分别在定制采集装置建立的102个人的2040张图像数据库上进行了16、32、64个子图像的测试。实验结果表明，分割LBP算法的性能优于原始LBP算法，圆形分割LBP算法的性能优于矩形分割LBP算法，当图像被分割为32个图像时，分割LBP算法的性能优于其他算法。
A new hand-dorsa vein recognition method based on Partition Local Binary Pattern (PLBP) is presented in this paper. The proposed method employs hand-dorsa vein images acquired from a low-cost, near infrared device. After preprocessing, the image is divided into sub-images. LBP uniform pattern features are extracted from all the sub-images, which are combined to form the feature vector for token vein texture features. The method is assessed using a similarity measure obtained by calculating the Chi square statistic between the feature vectors of the tested sample and the target sample. Integral histogram method, original LBP and Partition LBP with 16, 32, 64 sub-images are tested on a database of 2040 images from 102 individuals built up by a custom-made acquisition device. The experimental results show that Partition LBP performs better than original LBP, Circular Partition LBP performs better than Rectangular Partition LBP, and when the image was divided into 32 performs better than others.