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Due to the restriction of acquisition equipment and other reasons, the finger vein line appeared broken, torsion, translation and other deformation in local area. Therefore, the traditional methods got low recognition accuracy. In this paper, combining the advantages of modular method and bi-directional weighted B2DPCA with eigenvalue normalization; the bidirectional two-dimensional principal component...
Based on the characteristics of wavelet transform (WT), wavelet moment (WM), horizontal and vertical two-dimensional principal component analysis ((2D)2PCA), a new method of finger vein recognition is proposed. Firstly, the original images are decomposed into high-frequency and low-frequency components through WT, and the wavelet moment is extracted. Secondly the image feature matrix of low-frequency...
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