Earticle

초록

영어

Biometric methods have been played important roles in personal recognition during last twenty years. These methods include the face recognition, finger print and iris recognition. Recently iris imaging has many applications in security systems. The aim of this paper is to design and implement a new iris recognition algorithm. In this paper, the new feature extraction methods according to ridgelet transform and curvelet transform for identifying the iris images are provided. At first, after segmentation and normalization the collarette area of iris images has been extracted. Then we improve the quality of image by using median filter, histogram equalization, and the two-dimensional (2D) Wiener filter as well. Finally the ridgelet transform and curvelet transform are applied for extracting features and then the binary bit stream vectors are generated. The Hamming distance (HD) between the input bit stream vector and stored vectors is calculated for iris identification. The experimental results show efficiency of our proposed method.

목차

Abstract
 1. Introduction
 2. Iris Image Processing
  2.1. Segmentation
  2.2. Normalization
  2.3. Contrast Enhancement
 3. Feature Extraction
  3.1. Preliminary to Ridgelet and Curvelet Transforms
  3.2. Binary Codes
 4. Hamming Distance Classifier and Eye Rotation
  4.1. Hamming Distance Classifier
  4.2. Eye Rotation Problem
 5. Experimental Results
 6. Conclusion
 References

키워드

저자

• Mojtaba Najafi [ Electrical Engineering Department, Azad University, South Tehran Branch, Tehran, Iran. ]
• Sedigheh Ghofrani [ Electrical Engineering Department, Azad University, South Tehran Branch, Tehran, Iran. ] Corresponding author

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Signal Processing, Image Processing and Pattern Recognition

• 간기

  격월간

• pISSN

  2005-4254

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605