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Applied Computational Intelligence and Soft Computing
Volume 2013 (2013), Article ID 515918, 11 pages
Research Article

A Novel Algorithm for Feature Level Fusion Using SVM Classifier for Multibiometrics-Based Person Identification

1Department of Computer Technology, Yeshwantrao Chavan College of Engineering, Nagpur 441110, India
2Department of Computer Engineering, Sardar Vallabhbhai National Institute of Technology, Surat, India
3Nagar Yuwak Shikshan Sanstha, Nagpur, India

Received 1 April 2013; Revised 16 June 2013; Accepted 17 June 2013

Academic Editor: Zhang Yi

Copyright © 2013 Ujwalla Gawande et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Citations to this Article [5 citations]

The following is the list of published articles that have cited the current article.

  • Md. Rabiul Islam, “Feature and Score Fusion Based Multiple Classifier Selection for Iris Recognition,” Computational Intelligence and Neuroscience, vol. 2014, pp. 1–11, 2014. View at Publisher · View at Google Scholar
  • Jitendra P. Chaudhari, Vaibhav V. Dixit, Pradeep M. Patil, and Yogesh P. Kosta, “Multimodal biometric-information fusion using the Radon transform,” Journal of Electronic Imaging, vol. 24, no. 2, 2015. View at Publisher · View at Google Scholar
  • Satish S. Bhairannawar, K. B. Raja, and K. R. Venugopal, “An Efficient Reconfigurable Architecture for Fingerprint Recognition,” VLSI Design, vol. 2016, pp. 1–22, 2016. View at Publisher · View at Google Scholar
  • Kamal Hajari, Ujwalla Gawande, and Yogesh Golhar, “Neural Network Approach to Iris Recognition in Noisy Environment,” Procedia Computer Science, vol. 78, pp. 675–682, 2016. View at Publisher · View at Google Scholar
  • Lavinia Mihaela Dinca, and Gerahard Hancke, “The fall of one, the rise of many: A survey on multi-biometric fusion methods,” IEEE Access, pp. 1–1, 2017. View at Publisher · View at Google Scholar