전자공학회논문지 IE

The Institute of Electronics and Information Engineers (대한전자공학회)
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An Effective Crease Detection Method for Feature Information Extraction in Fingerprint Images

지문 영상의 특징 정보 추출을 위한 효율적인 주름선 추출 방법

  • Published : 2007.06.25
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Abstract

In this paper, the crease extraction method is proposed to improve the accuracy of feature extraction within the fingerprint image. First of all, for each pixel in fingerprint image, it calculates the average grey level and variance to determine if the current pixel composes the crease, and estimates the direction of crease. Secondly, once the direction of every pixel in crease candidate area is estimated, it is decomposed into 8 different images, depending on their direction. The properties of crease consists of the length of the crease candidate area, the correspondence between the crease direction and the pixel distribution direction, the difference between the ridge direction and the pixel distribution direction, and finally the grey level of the candidate pixels. The proposed method finally extracts the crease from the crease clusters estimated from directional images. In conclusion, applying the proposed method improved the accuracy of overall feature extraction by 91.4% by accurately and precisely extracting the crease from fingerprint image.

본 논문에서는 지문 영상 내부에서 특징 정보 추출의 정확성을 향상시킬 수 있는 주름선 검출 방법을 제안한다. 먼저 각 방향별 슬릿의 평균 픽셀 값과 분산에 의하여 픽셀이 주름선 후보 영역에 해당하는지를 결정하고, 그 위치에 해당하는 주름선 방향을 검출한다. 그리고 후보 영역에 해당하는 픽셀의 주름선 방향에 의하여 8개의 영상으로 분해한다. 각 방향별 분해 영상에서 주름선 후보 영역 픽셀들이 형성하는 클러스터의 길이, 주름선 방향과 픽셀 분포 방향의 일치성, 융선 방향과 픽셀 분포방향의 차, 후보 픽셀들의 평균 픽셀 값을 이용하여 주름선 클러스터를 검출한다. 마지막으로, 각 방향별 분해 영상의 주름선 클러스터들을 합성함으로써 주름선 영역을 검출한다. 제안한 방법을 구현하고 주름선 검출을 수행한 결과, 91.4%의 높은 정확성을 확인하였다.

Keywords

References

  1. L. C. Jain, U. Halici, I. Hayashi, S. B. Lee, and S. Tsutsui, Intelligent Biometric Techniques in Fingerprint and Face Recognition, CRC Press, 1999
  2. 김재희, '생체인식 심화학습-지문인식', 시큐리티 월드, pp.58-63, February 2001
  3. Asker M. Bazen and Sabih H. Gerez, 'Segmentation of Fingerprint Images', ProRISC 2001 Workshop on Circuits, Systems and Signal Processing, pp.475-479, November 2001
  4. Raymond Thai, Fingerprint Image Enhancement and Minutiae Extraction, The University of Western Australia, 2003
  5. Pontus Hyme'r, Extraction and Application of Secondary Crease Information in Fingerprint Recognition Systems, Linkoping University, Germany, March 2005
  6. Chenyu Wu, Jie Zhou, Zhao-qi Bian, Gang Rong, 'Robust Crease Detection in Fingerprint Images', Proceedings of the 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'03), Vol.2, pp.505-512, June 2003
  7. Anil K. Jain, Lin Hong, Yifei Wan, 'Fingerprint image enhancement : algorithm and performance evaluation', IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol.20, No.8, pp.777-789, August 1998 https://doi.org/10.1109/34.709565
  8. Anil K. Jain, Nalini K. Ratha, Shaoyun Chen, 'Adaptive flow orientation-based feature extraction in fingerprint images', Pattern Recognition, Vol.28, No.11, pp.1657-1672, 1995 https://doi.org/10.1016/0031-3203(95)00039-3
  9. C. L. Wilson, G. T. Candela, C. I. Watson, 'Neural-network fingerprint classification', Journal. of Artificial Neural Networks, Vol.1, No.2, pp.203-228, 1994
  10. Asker M. Bazen and Sabih H. Gerez, 'Systematic Methods for the Computation of the Directional Fields and Singular Points of Fingerprints', IEEE Trans. on Pattern Analysis Machine Intelligence, Vol.24, No.7, pp.905-919, July 2002 https://doi.org/10.1109/TPAMI.2002.1017618
  11. Xinjian Chen, Jie Tian, Jiangang Cheng, Xin Yang, 'Segmentation of Fingerprint Images Using Linear Classifier', EURASIP Journal on Applied Signal Processing, pp.480-494, 2004
  12. David D. Zhang, Biometric Solutions for Authentication in An E-World, Kluwer Academic Publishers, 2002
  13. R. H. Bamberger and M. J. T. Smith, 'A filter bank for the directional dcomposition of image: Theory and design', IEEE Trans. Signal Processing, Vol.40, No.4, pp.882-893, 1992 https://doi.org/10.1109/78.127960
  14. Jie Zhou, Jinwei Gu, 'A Model-Based Method for the Computation of Fingerprints' Orientation Field', IEEE Trans. on Image Processing, Vol.13, No.6, pp.821-835, June 2004 https://doi.org/10.1109/TIP.2003.822608
  15. S. Park, M. J. T. Smith, and R. M. Mersereau, 'A new directional filter bank for image analysis and classification', in Proc. ICASSP 1999, Vol.3, pp.1417-1420, 1999