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Multispectral palmprint recognition using multiclass projection extreme learning machine and digital shearlet transform

  • Extreme Learning Machine and Applications
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Abstract

A novel multispectral palmprint recognition method is proposed based on multiclass projection extreme learning machine (MPELM) and digital shearlet transform. Extreme learning machine (ELM) is a novel and efficient learning machine based on the generalized single-hidden-layer feedforward networks, which performs well in classification applications. Many researchers’ experimental results have shown the superiority of ELM with classical algorithm: support vector machine (SVM). To further improve the performance of multispectral palmprint recognition method, we propose a novel method based on MPELM in this paper. Firstly, all palmprint images are preprocessed by David Zhang’s method. Then, we use image fusion method based on fast digital shearlet transform to fuse the multispectral palmprint images. At last, we use the proposed MPELM classifier to determine the final multispectral palmprint classification. The experimental results demonstrate the superiority of multispectral fusion to each single spectrum, and the proposed MPELM-based method outperforms the SVM-based and ELM-based methods. The proposed method is also suitable for other biometric applications and gets to be work well.

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Acknowledgments

The work is supported by the grants from the National Natural Science Foundation of China (No. 0902025), the special financial grant from China Postdoctoral Science Foundation (2012T50807), the grants from China Postdoctoral Science Foundation (No. 20110491661), the grants from the Natural Science Foundation Funded Project of Jilin Province (No. 20130101055JC), the grants from the Industrial Technology Research and Development Special Project of Jilin Province (No. 2011006-9). the grants of The National Development and Reform Commission Project (No. CNGI-05-17-1T) and Huawei Innovation Research Program. Nanyang Technological University is thanked for providing ELM source code used in this study. Hong Kong Polytechnic University is thanked for providing multispectral palmprint database used in this study.

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Authors and Affiliations

  1. School of Electronics and Information Engineering, Xi’an Jiaotong University, 28 Xian’ning West Road, Xi’an, 710049, China

    Xuebin Xu, Longbin Lu, Xinman Zhang & Wanyu Deng

  2. School of Software Engineering, Changchun University of Technology, Changchun, 130012, China

    Huimin Lu

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  1. Xuebin Xu
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  2. Longbin Lu
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  3. Xinman Zhang
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  4. Huimin Lu
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  5. Wanyu Deng
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Correspondence to Xinman Zhang.

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Xu, X., Lu, L., Zhang, X. et al. Multispectral palmprint recognition using multiclass projection extreme learning machine and digital shearlet transform. Neural Comput & Applic 27, 143–153 (2016). https://doi.org/10.1007/s00521-014-1570-8

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  • DOI: https://doi.org/10.1007/s00521-014-1570-8

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