Fast near-infrared palmprint recognition using nonnegative matrix factorization extreme learning machine

• Autorzy: Xu X. , Zhang X. , Lu L. , Deng W. , Zuo K

Identyfikatory

DOI

10.5277/oa140209

• Języki publikacji: EN

Abstrakty

EN

Support vector machine and artificial neural network are widely used in classification applications. Extreme learning machine (ELM) is a novel and efficient learning algorithm based on the generalized single hidden layer feed forward networks, which performs well in classification applications. The research results have shown the superiority of ELM with the existing classical algorithms: support vector machine (SVM) and back propagation neural network. In this study, we firstly propose a novel nonnegative matrix factorization extreme learning machine (NMFELM) to improve the performance of standard ELM method. Then we propose a novel near-infrared palmprint recognition approach based on NMFELM classifier. As the test data, we use the near-infrared palmprint database provided by Hong Kong Polytechnic University. The experimental results demonstrate that the proposed NMFELM method outperforms the standard ELM- and SVM-based methods.

Słowa kluczowe

EN

extreme learning machine; palmprint recognition; superior speed; support vector machine (SVM)

• Wydawca: Oficyna Wydawnicza Politechniki Wrocławskiej
• Czasopismo: Optica Applicata
• Rocznik: 2014
• Tom: Vol. 44, nr 2
• Strony: 285--298
• Opis fizyczny: Bibliogr., 28 poz., rys., tab.

Twórcy

autor

Xu X.

• MOE Key Lab for Intelligent Networks and Network Security, School of Electronics and Information Engineering, Xi’an Jiaotong University, Xi’an, 710049, China

autor

Zhang X.

• MOE Key Lab for Intelligent Networks and Network Security, School of Electronics and Information Engineering, Xi’an Jiaotong University, Xi’an, 710049, China

autor

Lu L.

• MOE Key Lab for Intelligent Networks and Network Security, School of Electronics and Information Engineering, Xi’an Jiaotong University, Xi’an, 710049, China

autor

Deng W.

• MOE Key Lab for Intelligent Networks and Network Security, School of Electronics and Information Engineering, Xi’an Jiaotong University, Xi’an, 710049, China

autor

Zuo K

• Huawei Central Research Academy, Beijing, 100095, China

Bibliografia

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