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논문검색

Efficient Iris Recognition Method for Large Scale Database

초록

영어

In general, personal identification using the iris is means for identifying each individual by using the unique pattern of iris. Even twins have different iris pattern image, and each right eye and left eye has a different pattern for the same individual. Thus, the iris has the best characteristics that reflect the personal differences of the human body. In this paper, we proposed an efficient iris recognition method for large scale database. The Zernike moment is used for filtering out the candidate iris data from large scale database and the multiple SVM is applied for iris recognition. The proposed method proved to be an efficient searching method because the process did not match one-to-one feature data during the searching iris database.

목차

Abstract
 1. Introduction
 2. Processing
  2.1 Iris Area Extractions
  2.2 Iris Normalization
 3. Proposed Method
  3.1. Zernike Moment Extraction
  3.2. Filtering Zernike Moments (Filtering Stage)
  3.3. Screening of Zernike Moments (Decision phase)
  3.4. Recognition Using SVM
 4. Experimental Results and Discussion
  4.1. Performance Evaluation
  4.2. Experimental Methods
  4.3. Experiment Results
 5. Conclusion
 Reference

저자정보

  • Chang-Soo Choi Vocational Training Teacher, Cheongju Correction Institution, Cheongju, Chungbuk 361-754, Korea
  • Jeong-Man Seo Department of Game Contents, Korea National University of Welfare, Pyeongtaek, Gyeonggi-Do 459- 717, Korea
  • Heeman Lee Department of Multimedia, Seowon University, Cheongju, Chungbuk 362-742, Korea

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