Abstract
This chapter describes the problem of segmentation of overlapped fingerprints, which is a required prerequisite step in the fingerprint processing pipeline, performed before the processes of fingerprint separation and subsequent verification. Overlapped fingerprints segmentation is usually performed manually, and only recently there have been (semi-)automatic approaches proposed in the literature. The evaluation procedure to assess the quality of such approaches is also discussed.
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W. Bian, S. Ding, W. Jia, Collaborative filtering model for enhancing fingerprint image. IET Image Process. 12(1), 149–157 (2017)
A.P. Bradley, The use of the area under the ROC curve in the evaluation of machine learning algorithms. Pattern Recogn. 30(7), 1145–1159 (1997)
K. Cao, E. Liu, A. Jain, Segmentation and enhancement of latent fingerprints: a coarse to fine ridgestructure dictionary. IEEE Trans. Pattern Anal. Mach. Intell. 36(9), 1847–1859 (2014)
H. Choi, M. Boaventura, I.A. Boaventura, A.K. Jain, Automatic segmentation of latent fingerprints, in IEEE Fifth International Conference on Biometrics: Theory, Applications and Systems (BTAS) 2012 (IEEE, Piscataway, 2012), pp. 303–310
T. Fawcett, An introduction to ROC analysis. Pattern Recogn. Lett. 27(8), 861–874 (2006)
J. Feng, Y. Shi, J. Zhou, Robust and efficient algorithms for separating latent overlapped fingerprints. IEEE Trans. Inf. Forensics Secur. 7(5), 1498–1510 (2012)
M.D. Garris, R.M. McCabe, Fingerprint minutiae from latent and matching tenprint images, in Tenprint Images, (National Institute of Standards and Technology, 2000)
M. Ghafoor, I.A. Taj, W. Ahmad, N.M. Jafri, Efficient 2-fold contextual filtering approach for fingerprint enhancement. IET Image Process. 8(7), 417–425 (2014)
S. Karimi-Ashtiani, C.-C.J. Kuo, A robust technique for latent fingerprint image segmentation and enhancement, in 15th IEEE International Conference on Image Processing, 2008. ICIP 2008 (IEEE, Piscataway, 2008), pp. 1492–1495
A. Sankaran, A. Jain, T. Vashisth, M. Vatsa, R. Singh, Adaptive latent fingerprint segmentation using feature selection and random decision forest classification. Inf. Fusion 34, 1–15 (2017)
P. Schuch, S. Schulz, C. Busch, Survey on the impact of fingerprint image enhancement. IET Biom. 7(2), 102–115 (2017)
N.J. Short, M.S. Hsiao, A.L. Abbott, E.A. Fox, Latent fingerprint segmentation using ridge template correlation, in 4th International Conference on Imaging for Crime Detection and Prevention 2011 (ICDP 2011) (IET, Stevenage, 2011), pp. 1–6
B. Stojanović, O. Marques, A. Nešković, Latent overlapped fingerprint separation: a review. Multimed. Tools Appl. 76(15), 1–28 (2016)
B. Stojanović, O. Marques, A. Nešković, Deep learning-based approach to latent overlapped fingerprints mask segmentation. IET Image Process. 12(11), 1934–1942 (2018)
D.H. Thai, C. Gottschlich, Global variational method for fingerprint segmentation by three-part decomposition. IET Biom. 5(2), 120–130 (2016)
Q. Wang, J. Gao, Y. Yuan, Embedding structured contour and location prior in Siamesed fully convolutional networks for road detection. IEEE Trans. Intell. Transp. Syst. 19(1), 230–241 (2017)
Q. Wang, J. Gao, Y. Yuan, A joint convolutional neural networks and context transfer for street scenes labeling. IEEE Trans. Intell. Transp. Syst. 19(5), 1457–1470 (2017)
X. Yang, J. Feng, J. Zhou, S. Xia, Detection and segmentation of latent fingerprints, in 2015 IEEE International Workshop on Information Forensics and Security (WIFS) (IEEE, Piscataway, 2015), pp. 1–6
J. Zhang, R. Lai, C.-C.J. Kuo, Latent fingerprint segmentation with adaptive total variation model, in 2012 5th IAPR International Conference on Biometrics (ICB) (IEEE, Piscataway, 2012), pp. 189–195
J. Zhang, R. Lai, C.-J. Kuo, Latent fingerprint detection and segmentation with a directional total variation model, in 2012 19th IEEE International Conference on Image Processing (ICIP) (IEEE, Piscataway, 2012), pp. 1145–1148
J. Zhang, R. Lai, C.-C.J. Kuo, Adaptive directional total-variation model for latent fingerprint segmentation. IEEE Trans. Inf. Forensics Secur. 8(8), 1261–1273 (2013)
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Stojanović, B., Marques, O., Nešković, A. (2019). Overlapped Latent Fingerprints Segmentation: Problem Definition. In: Segmentation and Separation of Overlapped Latent Fingerprints. SpringerBriefs in Computer Science. Springer, Cham. https://doi.org/10.1007/978-3-030-23364-8_3
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DOI: https://doi.org/10.1007/978-3-030-23364-8_3
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