Person Identification Using Iris, Facial Image and Fingerprint with the Combined Algorithm of Principle Component Analysis and Singular Value Decomposition

Autores

  • A K M Akhtar Hossain Dept. of Computer Science and Engineering, University of Rajshahi,Rajshahi-6205, Bangladesh.
  • Md. Rokanujjaman Department of Computer Science and Engineering, University of Rajshahi, Rajshahi, Bangladesh
  • S.K. Ahmed Kamal Department of Applied Physics and Electronic Engineering, University of Rajshahi, Rajshahi, Bangladesh

Palavras-chave:

Multimodal biometrics, eigenspace, eigenfinger, eigeniris, eigenface, orthonormal vectors

Resumo

In this research, we consider three most important biometric features such as fingerprint, iris, and facial image to identify a person more precisely. Unimodal biometric system has several problems, such as noisy background data, non-universality and spoof attacks. Multimodal biometric systems can solve these limitations effectively by using two or more individual modalities. This system propose the Multimodal biometric systems on fingerprint, iris and facial image using combined algorithm of principle component analysis (PCA) and singular value decomposition (SVD) techniques. In this study, we found that the integrated output of the multimodal system represents better performance with respect to individual biometric features. Cite this ArticleA.K.M. Akhtar Hossain, Md. Rokanujjaman, S.K. Ahmed Kamal. Person Identification Using Iris, Facial Image and Fingerprint with the Combined Algorithm of Principle Component Analysis and Singular Value Decomposition. Journal of Computer Technology & Applications. 2017; 8(1): 29–34p.

Biografia do Autor

  • A K M Akhtar Hossain, Dept. of Computer Science and Engineering, University of Rajshahi,Rajshahi-6205, Bangladesh.
    Dept. of Computer Science and Engineering, University of Rajshahi,Rajshahi-6205, Bangladesh.

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Publicado

2017-04-21

Edição

Vol. 8 N.º 1 (2017)

Secção

Research Articles

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