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Palmprint Recognition Using Geometrical and Statistical Constraints

  • Aditya Nigam
  • Phalguni Gupta
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 236)

Abstract

This paper proposes an efficient biometrics system based on palmprint. Palmprint ROI is transformed using proposed local edge pattern (LEP). Corner like features are extracted from the enhanced palmprint images as they are stable and highly discriminative. It has also proposed a distance measure that uses some geometrical and statistical constraints to track corner feature points between two palmprint ROI’s. The performance of the proposed system is tested on publicly available PolyU database consisting of 7,752 and CASIA database consisting of 5,239 hand images. The feature extraction as well as matching capabilities of the proposed system are optimized and it is found to perform with CRR of \(99.97\,\%\) with ERR of \(0.66\,\%\) for PolyU and CRR of \(100\,\%\) with ERR of \(0.24\,\%\) on CASIA databases respectively.

Keywords

Biometrics Palmprint Local Binary Pattern (LBP) Phase only Correlation (POC) Optical Flow 

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Copyright information

© Springer India 2014

Authors and Affiliations

  1. 1.Indian Institute of TechnologyKanpurIndia

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