期刊
MULTIMEDIA TOOLS AND APPLICATIONS
卷 70, 期 3, 页码 2331-2345出版社
SPRINGER
DOI: 10.1007/s11042-012-1240-8
关键词
Palmprint recognition; Directional representation; Compressed sensing; Image processing
类别
资金
- National Natural Science Foundation of China [51175443, 61070163]
- Shandong Province Outstanding Research Award Fund for Young Scientists of China [BS2011DX034]
- Shandong Natural Science Foundation [ZR2011FQ030, ZR2011FM023]
In this paper, we propose a novel approach for palmprint recognition, which contains two interesting components: directional representation and compressed sensing. Gabor wavelets can be well represented for biometric image for their similar characteristics to human visual system. However, these Gabor-based algorithms are not robust for image recognition under non-uniform illumination and suffer from the heavy computational burden. To improve the recognition performance under the low quality conditions with a fast operation speed, we propose novel palmprint recognition approach using directional representations. Firstly, the directional representation for palmprint appearance is obtained by the anisotropy filter, which is robust to drastic illumination changes and preserves important discriminative information. Then, the principal component analysis (PCA) is used for feature extraction to reduce the dimensions of the palmprint images. At last, based on a sparse representation on PCA feature, the compressed sensing is used to distinguish palms from different hands. Experimental results on the PolyU palmprint database show the proposed algorithm have better performance than that of the Gabor based methods.
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