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Minimax Probability Machine for Iris Recognition

  • Yong Wang
  • Jiu-qiang Han
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3972)

Abstract

In this paper, a novel iris recognition method is proposed based on a state-of-the-art classification technique called minimax probability machine (MPM). Engaging the binary MPM technique, this work develops a multi-class MPM classification for reliable iris recognition with high accuracy. The experiments on iris database demonstrate that compared to the existent methods, the MPM-based iris recognition algorithm obtains better classification performance. It can significantly improve the recognition accuracy and has a competitive and promising performance.

Keywords

Gaussian Kernel Decision Boundary Iris Image Linear Kernel Iris Feature 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Yong Wang
    • 1
    • 2
  • Jiu-qiang Han
    • 1
  1. 1.School of Electronics and Information EngineeringXi’an Jiaotong UniversityXi’anP.R. China
  2. 2.School of Electronics EngineeringXidian UniversityXi’anP.R. China

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