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Research of Palmprint Recognition Based on 2DPCA

机译:基于2DPCA的掌纹识别研究

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A feature extraction method of palmprint recognition based on Two-Dimensional Principal Component Analysis (2DPCA) is proposed in this work. A series of experiments were performed on the PolyU- Online- Palmprint -Database with a nearest neighbor classifier and cosine distance. The recognition rate is 99.14%. The 2DPCA method has more recognition accuracy and more computationally efficient than PCA, especially in the small training samples. At the same time the selection of threshold has been researched in different application systems.
机译:提出了一种基于二维主成分分析(2DPCA)的掌纹识别特征提取方法。使用最近邻分类器和余弦距离,在PolyU-在线-掌上图数据库上进行了一系列实验。识别率为99.14%。 2DPCA方法比PCA具有更高的识别精度和更高的计算效率,尤其是在小的训练样本中。同时,已经在不同的应用系统中研究了阈值的选择。

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