Abstract
The fingerprint identification is a challenging task in criminal investigation due to less area of interest (ridges and valleys) in the fingerprint. In criminal incidences, the obtained fingerprints are often partial having less area of interest. Therefore, it is required to combine such partial fingerprints and make them entire such that it can be compared with stored fingerprint database for identification. The conventional phase correlation method is simple and fast, but the algorithm only works when the overlapping region is in the leftmost top corner in one of the two input images. However, it does not always happen in partial fingerprints obtained in forensic science. There are total six different possible positions of overlapping region in mosaiced fingerprint. The proposed algorithm solves the problem using the mirror image transformation of inputs and gives correct results for all possible positions of overlapping region.
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
Similar content being viewed by others
References
Zhang, D., Qijun, Z., Nan, L.U.O., Guangming, L.: Partial fingerprint recognition. U.S. Patent 8,411,913, issued April 2, 2013
Kuglin, C.D., Hines, D.C.: The phase correlation image alignment method. In: Proceedings of IEEE International Conference on Cybernetics Society, New York, pp. 163–165 (1975)
Reddy, B.S., Chatterji, B.N.: An FFT-based technique for translation, rotation and scale-invariant image registration. IEEE Trans. Image Process 5(8), 1266–1271 (1996)
Zhang, Y.-L., Yang, J., Wu, H.: A hybrid swipe fingerprint mosaicing scheme. In: Proceedings of International Conference on Audio and Video-based Biometric Person Authentication (AVBPA), Rye Brook, New York, pp. 131–140, July 2005
Tarar, S., Kumar, E.: Fingerprint mosaicing algorithm to improve the performance of fingerprint matching system. In: Computer Science and Information Technology, Horizon Research Publication Corporation, vol. 2, no. 3, pp. 142–151, Feb 2014
Jain, A.K., Ross, A.: Fingerprint mosaicing. In: Proceedings of IEEE International Conference on Acoustic, Speech, and Signal Process, vol. 4, pp. 4064–4067, May 2002
Ratha, N.K., Conell, J.H., Bolle, R.M.: Image mosaicing for rolled fingerprint construction. In: Proceedings of 4th International Conference Pattern Recognition, vol. 2, no. 8, pp. 1651–1653 (1998)
Shah, S., Ross, A., Shah, J., Crihalmeanu, S.: Fingerprint mosaicking using thin plate splines. In: Proceedings of Biometric Consortium Conference, Sept 2005
Choi, K., Choi, H., Lee, S., Kim, J.: Fingerprint image mosaicking by recursive ridge mapping. Special Issue on Recent Advances in Biometrics Systems. IEEE Trans. Syst. Man, Cybern. Part B: Cybern. 37(5), pp. 1191–1203 (2007)
Maltoni, D., Maio, D., Jain, A.K., Prabhakar, S.: Handbook of Fingerprint Recognition. Springer-Verlag, New York (2003)
Zuiderveld, K.: Contrast limited adaptive histogram equalization. Graphic Gems IV. Academic Press Professional Inc., San Diego, pp. 474–485 (1994)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer India
About this paper
Cite this paper
Bhati, S.H., Pati, U.C. (2016). Phase Correlation Based Algorithm Using Fast Fourier Transform for Fingerprint Mosaicing. In: Nagar, A., Mohapatra, D., Chaki, N. (eds) Proceedings of 3rd International Conference on Advanced Computing, Networking and Informatics. Smart Innovation, Systems and Technologies, vol 43. Springer, New Delhi. https://doi.org/10.1007/978-81-322-2538-6_52
Download citation
DOI: https://doi.org/10.1007/978-81-322-2538-6_52
Published:
Publisher Name: Springer, New Delhi
Print ISBN: 978-81-322-2537-9
Online ISBN: 978-81-322-2538-6
eBook Packages: EngineeringEngineering (R0)