A Comparative Study on Different Biometric Modals Using PCA

  • G. Pranay Kumar
  • Harendra Kumar Ram
  • Naushad Ali
  • Ritu Tiwari
Part of the Advances in Intelligent and Soft Computing book series (AINSC, volume 166)

Abstract

Multimodal Biometrics is a rising domain in biometric technology where more than one biometric trait is combined to improve the performance. It is well proved that multimodal biometrics has much higher efficiency than unimodal biometrics. In this research, a comparative study of multimodal biometrics has been done with four biometrics has been considered, three static, one behavioral namely face, ear, palm and gait respectively. The paper mainly focuses on four cases unimodal, bimodal, 3-modal, 4-modal biometrics and using PCA as the base feature extraction method in all cases. The training and testing algorithm has been embedded in PCA itself. the results of all cases are compared and that multimodal cases has much higher efficiency than unimodal and then comparing multimodal cases i.e. bi modal,3- modal,4-modal, there was not much difference and shows that, increasing the number of biometrics doesn’t make much difference.

Keywords

Multimodal biometric PCA Feature extraction Face Recognition Ear Recognition Palm Recognition Gait Recognition 

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Copyright information

© Springer-Verlag GmbH Berlin Heidelberg 2012

Authors and Affiliations

  • G. Pranay Kumar
    • 1
  • Harendra Kumar Ram
    • 1
  • Naushad Ali
    • 1
  • Ritu Tiwari
    • 1
  1. 1.ABV-Indian Institute of Information Technology and ManagementGwaliorIndia

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