Abstract
In order to make 3D fingerprints compatible with traditional 2D flat fingerprints, a common practice is to unfold the 3D fingerprint into a 2D rolled fingerprint, which is then matched with the flat fingerprints by traditional 2D fingerprint recognition algorithms. The problem with this method is that there may be large elastic deformation between the unfolded rolled fingerprint and flat fingerprint, which affects the recognition rate. In this paper, we propose a pose-specific 3D fingerprint unfolding algorithm to unfold the 3D fingerprint using the same pose as the flat fingerprint. Our experiments show that the proposed unfolding algorithm improves the compatibility between 3D fingerprint and flat fingerprint and thus leads to higher genuine matching scores.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Maltoni, D., Maio, D., Jain, A.K., Prabhakar, S.: Handbook of Fingerprint Recognition. Springer, London (2009). https://doi.org/10.1007/978-1-84882-254-2
Kumar, A.: Individuality of 3D fingerprints. In: Contactless 3D Fingerprint Identification. ACVPR, pp. 109–119. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-67681-4_8
Chen, Y., Parziale, G., Diaz-Santana, E., Jain, A.K.: 3D touchless fingerprints: Compatibility with legacy rolled images. In: Biometrics Symposium: Special Session on Research at the Biometric Consortium Conference, pp. 1–6. IEEE (2006)
Zhao, Q., Jain, A., Abramovich, G.: 3D to 2D fingerprints: unrolling and distortion correction. In: International Joint Conference on Biometrics (IJCB), pp. 1–8. IEEE (2011)
Labati, R.D., Genovese, A., Piuri, V., Scotti, F.: Quality measurement of unwrapped three-dimensional fingerprints: a neural networks approach. In: International Joint Conference on Neural Networks (IJCNN), pp. 1–8. IEEE (2012)
Wang, Y., Lau, D.L., Hassebrook, L.G.: Fit-sphere unwrapping and performance analysis of 3D fingerprints. Appl. Opt. 49(4), 592–600 (2010)
Anitha, R., Sesireka, N.: Performance improvisation on 3D converted 2D unraveled fingerprint. IOSR J. Comput. Eng. (IOSR-JCE) 16(6), 50–56 (2014)
Wang, Y., Hassebrook, L.G., Lau, D.L.: Data acquisition and processing of 3-D fingerprints. IEEE Trans. Inf. Forensics Secur. 5(4), 750–760 (2010)
Labati, R.D., Genovese, A., Piuri, V., Scotti, F.: Fast 3-D fingertip reconstruction using a single two-view structured light acquisition. In: IEEE Workshop on Biometric Measurements and Systems for Security and Medical Applications (BIOMS), pp. 1–8. IEEE (2011)
Dighade, R.R.: Approach to unwrap a 3D fingerprint to a 2D equivalent. University of Maryland, Master Thesis (2012)
Fatehpuria, A., Lau, D.L., Hassebrook, L.G.: Acquiring a 2D rolled equivalent fingerprint image from a non-contact 3D finger scan. In: Biometric Technology for Human Identification III. Volume 6202, International Society for Optics and Photonics, vol. 62020C (2006)
Shafaei, S., Inanc, T., Hassebrook, L.G.: A new approach to unwrap a 3-D fingerprint to a 2-D rolled equivalent fingerprint. In: IEEE 3rd International Conference on Biometrics: Theory, Applications, and Systems (BTAS), pp. 1–5. IEEE (2009)
Bazen, A.M., Gerez, S.H.: Fingerprint matching by thin-plate spline modelling of elastic deformations. Pattern Recogn. 36(8), 1859–1867 (2003)
Ross, A., Shah, S., Shah, J.: Image versus feature mosaicing: a case study in fingerprints. In: Biometric Technology for Human Identification III. Volume 6202, International Society for Optics and Photonics, vol. 620208 (2006)
Cheng, X., Tulyakov, S., Govindaraju, V.: Minutiae-based matching state model for combinations in fingerprint matching system. In: CVPR Workshop on Biometrics, pp. 92–97 (2013)
Si, X., Feng, J., Yuan, B., Zhou, J.: Dense registration of fingerprints. Pattern Recogn. 63, 87–101 (2017)
Cui, Z., Feng, J., Li, S., Lu, J., Zhou, J.: 2-D phase demodulation for deformable fingerprint registration. IEEE Trans. Inf. Forensics Secur. 13(12), 3153–3165 (2018)
Cappelli, R., Ferrara, M., Maltoni, D.: Minutia cylinder-code: a new representation and matching technique for fingerprint recognition. IEEE Trans. Pattern Anal. Mach. Intell. 32(12), 2128–2141 (2010)
Neurotechnology Inc., VeriFinger. http://www.neurotechnology.com
Leordeanu, M., Hebert, M.: A spectral technique for correspondence problems using pairwise constraints. In: International Conference on Computer Vision (ICCV) (2005)
Acknowledgments
This work was supported in part by the National Natural Science Foundation of China under Grant 61976121.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2021 Springer Nature Switzerland AG
About this paper
Cite this paper
Guan, X., Feng, J., Zhou, J. (2021). Pose-Specific 3D Fingerprint Unfolding. In: Feng, J., Zhang, J., Liu, M., Fang, Y. (eds) Biometric Recognition. CCBR 2021. Lecture Notes in Computer Science(), vol 12878. Springer, Cham. https://doi.org/10.1007/978-3-030-86608-2_21
Download citation
DOI: https://doi.org/10.1007/978-3-030-86608-2_21
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-86607-5
Online ISBN: 978-3-030-86608-2
eBook Packages: Computer ScienceComputer Science (R0)