基于子空间与纹理特征融合的掌纹识别 下载: 1062次
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.
李新春, 马红艳, 林森. 基于子空间与纹理特征融合的掌纹识别[J]. 激光与光电子学进展, 2019, 56(7): 071007. Xinchun Li, Hongyan Ma, Sen Lin. Palmprint Recognition Based on Subspace and Texture Feature Fusion[J]. Laser & Optoelectronics Progress, 2019, 56(7): 071007.