Abstract
Singular point (SP) extraction is a key component in automatic fingerprint identification system (AFIS). A new method was proposed for fingerprint singular points extraction, based on orientation tensor field and Laurent series. First, fingerprint orientation flow field was obtained, using the gradient of fingerprint image. With these gradients, fingerprint orientation tensor field was calculated. Then, candidate SPs were detected by the cross-correlation energy in multi-scale Gaussian space. The energy was calculated between fingerprint orientation tensor field and Laurent polynomial model. As a global descriptor, the Laurent polynomial coefficients were allowed for rotational invariance. Furthermore, a support vector machine (SVM) classifier was trained to remove spurious SPs, using cross-correlation coefficient as a feature vector. Finally, experiments were performed on Singular Point Detection Competition 2010 (SPD2010) database. Compared to the winner algorithm of SPD2010 which has best accuracy of 31.90%, the accuracy of proposed algorithm is 45.34%. The results show that the proposed method outperforms the state-of-the-art detection algorithms by large margin, and the detection is invariant to rotational transformations.
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BAZEN A M, GEREZ S H. Systematic methods for the computation of the directional fields and singular points of fingerprints [J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2002, 24(7): 905–918.
FAN Ling-ling, WANG Shu-guang, WANG Hong-fa, GUO Tian-de. Singular points detection based on Zero-Pole model in fingerprint images [J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2008, 30(6): 929–940.
WANG Lin, DAI Mo. Localization of singular points in fingerprint images based on the Gaussian-Hermite moments [J]. Journal of Software, 2006, 17(2): 242–249.
NILSSON K, BIGUN J. Localization of corresponding points in fingerprints by complex filtering [J]. Pattern Recognition Letters, 2003, 24(13): 2135–2144.
LIU M H. Fingerprint retrieval by complex filter responses [C]// 18th International Conference on Pattern Recognition (ICPR’06). Washington D C: IEEE Computer Society Press, 2006: 1042–1045.
LI J, YAU W Y, WANG H. Combining singular points and orientation image information for fingerprint classification [J]. Pattern Recognition, 2008, 41(1): 353–366.
LIU M H. Fingerprint classification based on adaboost learning from singularity features [J]. Pattern Recognition, 2010, 43(3): 1062–1070.
LIU W, ERALDO R. Scale and rotation Invariant detection of singular patterns in vector flow fields [C]// IAPR International Workshop on Structural Syntactic Pattern Recognition (S-SSPR). Berlin: Springer-Verlag, 2010: 522–531.
DASS S C. Markov random field models for directional field and singularity extraction in fingerprint images [J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2004, 13(10): 1358–1367.
PARAK C H, LEEB J J, MARK J. T. SMITHA, PARKC K H. Singular point detection by shape analysis of directional fields in fingerprints [J]. Pattern Recognition, 2006, 39(5): 839–855.
WANG Y, HU J K, PHILLIPS D. A Fingerprint orientation model based on 2D Fourier expansion (FOMFE) and its application to singular-point detection and fingerprint indexing [J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2007, 29(4): 573–584.
ANIL J, LIN H, SHARATH P. Filterbank-based fingerprint matching [J]. IEEE Transactions on Image Processing, 2000, 9(5): 846–859.
SHARAT C, CARTWRIGHT A N, GOVINDARAJU V. Fingerprint enhancement using STFT analysis [J]. Pattern Recognition, 2007, 40(1): 198–211.
HONG L, WAN Y, JAIN A K. Fingerprint image enhancement: algorithm and performance evaluation [J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1998, 20(8): 777–789.
SSERLOCK B G, MONRO D M. A model for interpreting fingerprint topology [J]. Pattern Recognition, 1993, 26(7): 1047–1055.
LI Hong, XIE Song-fa. Functions of complex variable and integral transforms [M]. Beijing: Higher Education Press, 2006: 88–100. (in Chinese)
LINDEBERG T. Scale-space theory: A basic tool for analysing structures at different scales [J]. Journal of Applied Statistics, 1994, 21 (s2): 224–270.
ZHANG A Q, HONG Y. Fingerprint classification based on extraction and analysis of singularities and pseudo ridges [J]. Pattern Recognition, 2004, 37(11): 2233–2243.
HASTINGS R O. Disambiguation of fingerprint ridge flow direction-two approaches [C]// 16th Scandinavian Conference on Image Analysis. Berlin: Springer-Verlag, 2009: 530–539.
ICIAR 2010. Singular Points Detection Competition SPD2010 [EB/OL]. [2012-6-13]. http://paginas.fe.up.pt/~spd2010/home.html.
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Foundation item: Project(11JJ3080) supported by Natural Science Foundation of Hunan Province, China; Project(11CY012) supported by Cultivation in Hunan Colleges and Universities, China; Project(ET51007) supported by Youth Talent in Hunan University, China
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Liu, Q., Peng, K., Liu, W. et al. Fingerprint singular points extraction based on orientation tensor field and Laurent series. J. Cent. South Univ. 21, 1927–1934 (2014). https://doi.org/10.1007/s11771-014-2139-5
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DOI: https://doi.org/10.1007/s11771-014-2139-5