Palmprint Recognition Based on Subspace and Texture Feature Fusion

Xinchun Li; Hongyan Ma; Sen Lin

doi:10.3788/LOP56.071007

Journals >Laser & Optoelectronics Progress >Volume 56 >Issue 7 >Page 071007 > Article

Laser & Optoelectronics Progress
Vol. 56, Issue 7, 071007 (2019)

Palmprint Recognition Based on Subspace and Texture Feature Fusion

Xinchun Li¹, Hongyan Ma^2、*, and Sen Lin¹

Author Affiliations

¹ School of Electronic and Information Engineering, Liaoning Technical University, Huludao, Liaoning 125105, China

² Postgraduate College, Liaoning Technical University, Huludao, Liaoning 125105, China

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DOI: 10.3788/LOP56.071007 Cite this Article Set citation alerts

Xinchun Li, Hongyan Ma, Sen Lin. Palmprint Recognition Based on Subspace and Texture Feature Fusion[J]. Laser & Optoelectronics Progress, 2019, 56(7): 071007 Copy Citation Text

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Fig. 1. Coding principle of LOBP

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Fig. 2. Flow chart for extracting palmprint texture features by LOBP

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Fig. 3. Flow chart of palmprint recognition

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Fig. 4. Examples of databases. (a) PolyU database; (b) self-built non-contact database

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Fig. 5. Experimental results on PolyU database. (a) Matching results; (b) ROC

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Fig. 6. Experimental results on self-built non-contact database. (a) Matching results; (b) ROC

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Fig. 7. Comparison of EER between proposed method and latest methods

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Fig. 8. Comparison of recognition rate between proposed method and latest methods

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Input: data matrix X, parameter λ₁
Initialization:A=0; E=0; Y=0; α=0.1; ρ=1.01;P=arg $\begin{matrix} \min_{P} \end{matrix}$ tr $\begin{matrix} [P^{T} (S_{w} - λ S_{b}) P] \end{matrix}$ s.t. P^TP=I;α_max=10⁵;λ=10^-4
while not converged do1. Update A by using Eq. (17);2. Update P by using Eq. (19);3. Update E by using Eq. (21);4. Update Y, α by using Eqs. (22) and (23), respectively
end while
Output: P,A,E

Table 1. Summary of RLDA algorithm

Database	Subspacefeature	Texturefeature	Fusionfeature
PolyU	1.5082	0.3853	0.3440
Self-builtnon-contact	2.5176	1.5168	1.4922

Table 2. EER for single feature and fusion feature recognitions%

Method	PolyUdatabase		Self-built non-contactdatabase
Method	EER /%	Recognitiontime /s	EER /%	Recognitiontime /s
PCA	3.5064	0.3165	5.6432	0.3091
2DGabor	2.5242	0.8189	3.1340	0.9136
LDA	3.2340	0.2674	4.3759	0.3010
LBP	3.1754	0.2424	4.2591	0.2911
RLDA	1.5082	0.2229	2.5176	0.2294
LOBP	0.3853	0.1628	1.5168	0.1801
LBP+2DLPP^[9]	0.5077	0.4844	1.6326	0.5794
GGF^[10]	0.4761	0.3505	1.6073	0.3968
WACS-LBP+WSRC^[11]	0.4085	0.3239	1.5384	0.3479
ProposedRLDA+LOBP	0.3440	0.3069	1.4922	0.3127

Table 3. Comparison of EER and recognition time between proposed and other methods

Xinchun Li, Hongyan Ma, Sen Lin. Palmprint Recognition Based on Subspace and Texture Feature Fusion[J]. Laser & Optoelectronics Progress, 2019, 56(7): 071007

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