Abstract
A common problem in fingerprint recognition is the existence of false minutiae which increase both FAR and FRR in fingerprint matching. In this paper, a robust minutiae postprocessing algorithm is proposed. Unlike most algorithms which use simple distance and connectivity criterions for postprocessing, we also used orientation and flow of ridges as the key factor for postprocessing to avoid eliminating true minutiae while postprocessing. It is shown by the experiments that our postprocessing algorithm improves the minutiae extraction accuracy and the performance of the matching process.
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References
D. Maio and D. Maltoni, “Direct Gray-Scale Minutiae Detection in Fingerprints,” IEEE Trans. Pattern Anal. Machine Intell., vol. 19,no. 1, pp. 27–39, 1997.
A.K. Jain, L. Hong, and R. Bolle, “On-Line Fingerprint Verification,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 19,no. 4, pp.302–313, April 1997.
L.C. Jain et al. Eds., Intelligent Biometric Techniques in Fingerprint and Face Recognition, CRC Press International Series on Computational Intelligence, 1999.
N.K. Ratha, S. Chen, and A.K. Jain, “Adaptive Flow Orientation Based Feature Extraction in Fingerprint Images,” Pattern Recognition, vol. 28,no. 11, pp. 1,657–1,672, 1995.
Q. Xiao and H. Raafat, “Fingerprint Image Postprocessing: A Combined Statistical and Structural Approach,” Pattern Recognition, vol. 28,no. 11, pp. 1,657–1,672, 1995.
L. Hong, Y. Wan, and A.K. Jain, “Fingerprint Image Enhancement: Algorithm and Performance Evaluation,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol.20, pp.777–789, Aug. 1998.
J.R. Parker, Algorithms for Image Processing and Computer Vision, New York: Wiley Computer Publishing, 1997.
A. Wahab, S.H. Chin, and E.C. Tain, “Novel Approach to Automated Fingerprint Recognition,” IEE Proc.-Vis. Image Signal Process, vol.145,no.3, pp.160–166, Jun. 1998.
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© 2001 Springer-Verlag Berlin Heidelberg
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Kim, S., Lee, D., Kim, J. (2001). Algorithm for Detection and Elimination of False Minutiae in Fingerprint Images. In: Bigun, J., Smeraldi, F. (eds) Audio- and Video-Based Biometric Person Authentication. AVBPA 2001. Lecture Notes in Computer Science, vol 2091. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45344-X_34
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DOI: https://doi.org/10.1007/3-540-45344-X_34
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