An Algorithm for Filtering False Minutiae in Fingerprint Recognition and its Performance Evaluation

지문의 의사 특징점 제거 알고리즘 및 성능 분석

  • Yang, Ji-Seong (Dept.of Operation Engineering, Inha University) ;
  • An, Do-Seong (Dept.of Operation Engineering, Inha University) ;
  • Kim, Hak-Il (Dept.of Operation Engineering, Inha University)
  • 양지성 (인하대학교 자동화공학과) ;
  • 안도성 (인하대학교 자동화공학과) ;
  • 김학일 (인하대학교 자동화공학과)
  • Published : 2000.05.01


In this paper, we propose a post-processing algorithm to remove false minutiae which decrease the overall performance of an automatic fingerprint identification system by increasing computational complexity, FAR(False Acceptance Rate), and FRR(False Rejection Rate) in matching process. The proposed algorithm extracts candidate minutiae from thinned fingerprint image. Considering characteristics of the thinned fingerprint image, the algorithm selects the minutiae that may be false and located in recoverable area. If the area where the selected minutiae reside is thinned incorrectly due to noise and loss of information, the algorithm recovers the area and the selected minutiae are removed from the candidate minutiae list. By examining the ridge pattern of the block where the candidate minutiae are found, true minutiae are recovered and in contrast, false minutiae are filtered out. In an experiment, Fingerprint images from NIST special database 14 are tested and the result shows that the proposed algorithm reduces the false minutiae extraction rate remarkably and increases the overall performance of an automatic fingerprint identification system.


  1. A.K. Jain, R. Bolle, and S. Pankanti, eds.,Biometrics : Personal Identification in Networked Society. Norwell, Mass.: Kluwer Academic Publisher, 1999
  2. D. Maio, and D. Maltoni, 'Direct Gray-Scale Minutiae Detection in Fingerprints,' IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 19, no. 1, pp. 27-39, Jan., 1999
  3. A.K. Jain, L. Hong, R. Bolle, 'On-Line Fingerprint Verification,' IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 19, no. 4, pp. 302-313, April., 1997
  4. 김현, 김학일, 'RSTI 불변 지문 인식 알고리즘,' 전자 공학회 논문지, 제35권, S편, 제6호, pp. 838-850, 1998. 6
  5. Q. Xiao and H. Raafat, 'Fingerprint image postprocessing : a combined statistical and structural approach,' Pattern Recognition, vol. 24, no. 10, pp. 985-992, 1991
  6. A. Farina, Z.M. Kovacs-Vajna, Alberto Leone, 'Fingerprint minutiae extraction from skeletonized binary images,' Pattern Recognition, vol.32, no. 4, pp. 877-889, 1999
  7. D. Maio and D. Maltoni, 'Neural Network Based Minutiae Filtering in Fingerprints,' Proceedings 14th ICPR, Brisbane(Australia), pp. 1654-1658, Aug.,1998
  8. N.K. Ratha, S. Chen ,A.K. Jain, 'Adaptive Flow Orientation-based Feature Extraction in Fingerprint Images,' Pattern Recognition, vol. 28, no. 11, pp. 1657-1672, 1995
  9. L. Hong, Y. Wan, and A.K. Jain, 'Fingerprint Image Enhancement Algorithm and Performance Evaluation,' IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 20, no. 8, pp. 777-789, Aug., 1998
  10. 안도성, 김학일, '클릭 구조를 이용한 지문 인식 알고리즘', 전자 공학회 논문지, 제36권, S편, 제5호, pp. 69-80, 1999. 2
  11. N.K. Ratha, K. Karu, S.Chen, A.k. Jain, 'A Real-Time Matching System for Large Fingerprint Database,' IEEE Trans. Pattern Analysis and Machine Intelligence, vol.18, no. 8, pp. 799-813, Aug. 1996
  12. B.M. Mehtre, N.K. Murthy, S. Kapoor, 'Segmentation of Fingerprint Using the Directional Image,' Pattern Recognition, Vol. 20, No. 4, pp. 429-435, 1987