Laser & Optoelectronics Progress, Volume. 56, Issue 7, 071007(2019)
Palmprint Recognition Based on Subspace and Texture Feature Fusion
ing at the problem of low recognition rate because the single descriptor cannot accurately obtain the effective palmprint features, a palmprint recognition method is proposed based on subspace and texture feature fusion. The subspace feature and texture feature of a palmprint image are obtained by robust linear discriminant analysis and local direction binary pattern, respectively. The weighted concatenation method is used for the subspace and texture feature fusion. The chi-square distance among the fused feature vectors is used for identification matching. The experimental results on the PolyU and the self-built non-contact databases show that the recognition time is 0.3069 s and 0.3127 s, respectively, and the lowest equal error rate is only 0.3440% and 1.4922%, respectively. Compared with other methods, the proposed method can accurately obtain the effective feature information of a palmprint image and improve the system recognition performance under the premise that the real-time performance is ensured.
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Xinchun Li, Hongyan Ma, Sen Lin. Palmprint Recognition Based on Subspace and Texture Feature Fusion[J]. Laser & Optoelectronics Progress, 2019, 56(7): 071007
Category: Image Processing
Received: Sep. 19, 2018
Accepted: Oct. 30, 2018
Published Online: Jul. 30, 2019
The Author Email: Ma Hongyan (1809282140@qq.com)