3D palmprint recognition based on local orientation binary pattern combined with collaborative representation

Table 1. Surface type
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Table 1. Surface type
GC>0 GC=0 GC<0
MC<0 Peak（STC=1） Ridge（STC=2） Saddle Ridge（STC=3）
MC=0 None（STC=4） Flat（STC=5） Minimal Surface（STC=6）
MC>0 Pit（STC=7） Valley（STC=8） Saddle Valley（STC=9）

Table 2. Experiment of block partitioning method
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Table 2. Experiment of block partitioning method
分块方式识别率/%
1 $\times$ 1 76.69
2 $\times$ 2 78.33
3 $\times$ 3 80.45
4 $\times$ 4 86.93
5 $\times$ 5 90.58
6 $\times$ 6 93.98
7 $\times$ 7 97.95
8 $\times$ 8 99.29
9 $\times$ 9 99.16
10 $\times$ 10 98.74

Table 3. Comparison of accuracy of different palmprint recognition methods

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Table 3. Comparison of accuracy of different palmprint recognition methods

N	MCI_Comp	MCI_Ordinal	MCI_GCI_ST	SI_Comp_LTP	ST_CR	ST_PCA	PDC	Proposed
1	87.16	83.12	80.99	82.84	90.51	93.76	94.41	95.53
2	94.90	93.09	92.09	93.46	95.10	98.69	98.74	99.04
3	96.86	93.86	95.06	95.33	97.83	99.18	99.32	99.44
4	98.75	97.95	97.50	97.42	98.36	99.39	99.48	99.55

Table 4. Comparison of methods based on collaborative representation
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Table 4. Comparison of methods based on collaborative representation
分类方法识别率/% 识别时间/s
CR_L1_SpaRSA 98.94 52.463 7
CR_L1_DALM 99.17 19.145 7
CR_L1_Homotopy 99.22 1.334 8
Proposed 99.29 0.874 9

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Yu-zhen LIU, Xiang-ji FAN, Sen LIN, Zhi-yong TAO. 3D palmprint recognition based on local orientation binary pattern combined with collaborative representation[J]. Chinese Journal of Liquid Crystals and Displays, 2022, 37(6): 726

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