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A Novel Approach for Iris Recognition Using Local Edge Patterns

  • Jen-Chun Lee
  • Ping S. Huang
  • Chien-Ping Chang
  • Te-Ming Tu
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4842)

Abstract

This paper presents an effective approach for iris recognition by analyzing the iris patterns. We propose an iris classification method that divides the normalized iris image into several regions to avoid the iris image with several noise factors (eyelids and eyelashes) and reduce the error rates. In every region, effective features are extracted by the proposed method of local edge pattern (LEP) for edge and corner detection. Feature vectors are linearly combined into a two dimensional matrix that represents every iris image for further recognition. Then 2D linear discriminant analysis (2DLDA) is used to identify the person. We use two public and freely available iris image databases for evaluation, organized in training and test sets respectively. Experimental results show that the recognition rate of the two iris image databases have achieved similar performance more than 98% and the proposed method has an encouraging performance and robustness.

Keywords

Feature Vector Iris Image Iris Recognition Correct Recognition Rate Iris Database 
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 2007

Authors and Affiliations

  • Jen-Chun Lee
    • 1
  • Ping S. Huang
    • 2
  • Chien-Ping Chang
    • 1
  • Te-Ming Tu
    • 1
  1. 1.Department of Electrical and Electronic Engineering, Institute of Technology, National Defense University, TaoyuanTaiwan
  2. 2.Department of Electronic Engineering, Ming Chuan University, TaoyuanTaiwan

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