Journal of the Institute of Electronics Engineers of Korea SP (대한전자공학회논문지SP)

The Institute of Electronics and Information Engineers (대한전자공학회)
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Robust Fingerprint Verification By Selective Ridge Matching

선택적 융선 정합에 의한 강건한 지문 인증기법

  • Park, Young-Tae (School of Electronics & Information Kyung Hee University)
  • 박영태 (경희대학교 전자정보학부)
  • Published : 2000.09.25
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Abstract

Point pattern matching schemes for finger print recognition do not guarantee robust matching performance for fingerprint Images of poor quality We present a finger print recognition scheme, where transformation parameters of matched ridge pairs are estimated by Hough transform and the matching hypothesis is verified by a new measure of the matching degree using selective directional information Proposed method may exhibit extremely low FAR(False accept rate) while maintaining low reject rate even for the Images of poor quality because of the robustness to the variation of minutia points.

지문인식의 주요 기법으로 사용되어 온 점 패턴 정합 기법은 영상의 질이 열악할 경우 정합 결과의 신뢰성을 보장하기 어려운 단점이 있다 본 논문에서는 유사한 융선 패턴 쌍의 변환 파라메터를 Hough 변환에 의해 산출하여 정합 쌍을 구하고 지문 방향정보를 선택적으로 사용하는 정합률 산출기법에 의해 정합 결과의 검증하는 지문언식 기법을 제안하였다 제안한 기법은 특이점의 개수와 좌표의 변화에 민감하지 않은 특성을 가지므로 열악한 지문영상에서도 낮은 거부율을 유지하면서 0%에 가까운 FAR(False accept rate)를 보장할 수 있다.

Keywords

References

  1. K. Karu and A. K. Jain, 'Fingerprint Classification,' Pattern Recognition, vol 29, no. 3, pp 389-404, (1996) https://doi.org/10.1016/0031-3203(95)00106-9
  2. A. K. Jain, L. Hong, R. Bolle, 'On-Lme Fingerprint Verification' IEEE Transaction on Pattern Analysis and Machine Intelligence Vol 19, No 4, pp 302-313, (1997) https://doi.org/10.1109/34.587996
  3. N Ansan, M. Chen, and, E Hou, 'A Genetic Algorithm for Point Pattern Matching.' Chapt 13, B Soucek and the IRIS Group, eds, Dynamic, Genetic, and Chaotic Programming New York: John Wiley & Sons, (1992)
  4. A Ranade and A Rosenfeld, 'Point Pattern matching by Relaxation,' Pattern Recognition, vol. 12, no 2, pp. 269-275, (1993)
  5. G Stockman, S Kopstenin, and S Benett, 'Matching Images to Models for Registration and Object Detection via Clustering,' IEEE Transaction on Pattern Analysis and Machine Intelligence, vol.4, no 3, pp.229-241, (1982)
  6. H. Lee and R Gaensslen, eds, Advances in Fingerprint Technology New York Elsevier, (1991)
  7. D Sherlock, D. Monro, and K. Millard, 'Fingerprint Enhancement by Directional Fourier Filtering.' IEE Proc. Vis Image Signal Processing, vol 141, no. 2, pp .87-94, (1994)
  8. G Candela, P Grother, C Watson, R. Wikinson, and C Wilson, 'PCASYS - A Pattern-level Classification Automation System for Fingerprints,' Technical Report, National Institute of Standards and Technology, Aug (l995)
  9. T Pavlidis, Algorithms for Graphics and Image Processing, Computer Science Press (1982)