Abstract
In this paper, we propose a novel online newborn personal authentication system based on footprint recognition. Compared with traditional offline footprinting scheme, the proposed system can capture digital footprint images with high quality. We also develop a preprocessing method for orientation and scale normalization. In this way, a coordinate system is defined to align the images and a region of interest (ROI) is cropped. In recognition stage, several representative subspace learning methods such as PCA, LDA are exploited for recognition. A newborn footprint database is established to examine the performance of the proposed system, and the promising experimental results demonstrate the effectiveness of proposed system.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Jain, A.K., Ross, A., Prabhakar, S.: An Introduction to Biometric Recognition. IEEE Transactions on Circuits and Systems for Video Technology. Special Issue on Image and Video based Biometrics 14(1), 4–20 (2004)
Weingaertner, D., Bello, O., Silva, L.: Newborn’s Biometric Identification: Can It Be Done? In: Proceedings of the VISAPP, vol. (1), pp. 200–205 (2008)
Nakajima, K., Mizukami, Y., Tanaka, K., Tamura, T.: Footprint-based Personal Recognition. IEEE Transactions on Biomedical Engineering 47(11), 1534–1537 (2000)
Belhumeur, P., Hespanha, K.: Eigenfaces vs. Fisherfaces: Recognition Using Class Specific Linear Projection. IEEE Trans. Pattern Anal. Mach. Intell. 19(7), 711–720 (1997)
Yang, J., Zhang, D., Frangi, A., Yang, J.: Two-Dimensional PCA: A New Approach to Appearance-Based Face Representation and Recognition. IEEE Trans. Pattern Analysis and Machine Intelligence 26(1), 131–137 (2004)
Li, M., Yuan, B.: 2D-LDA: A Novel Statistical Linear Discriminant Analysis for Image Matrix. Pattern Recognition Letter 26(5), 527–532 (2005)
Xu, D., Yan, S., Zhang, L., Lin, S., Zhang, H., Huang, T.: Reconstruction and Recognition of Tensor-based Objects with Concurrent Subspaces Analysis. IEEE Trans. on Circuits Systems for Video Technology 18(1), 36–47 (2008)
Yan, S., Xu, D., Yang, Q., Zhang, L., Tang, X., Zhang, H.: Multilinear Discriminant Analysis for Face Recognition. IEEE Trans. on Image Processing 16(1), 212–220 (2007)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Jia, W., Gui, J., Hu, RX., Lei, YK., Xiao, XY. (2010). Newborn Footprint Recognition Using Subspace Learning Methods. In: Huang, DS., Zhao, Z., Bevilacqua, V., Figueroa, J.C. (eds) Advanced Intelligent Computing Theories and Applications. ICIC 2010. Lecture Notes in Computer Science, vol 6215. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-14922-1_55
Download citation
DOI: https://doi.org/10.1007/978-3-642-14922-1_55
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-14921-4
Online ISBN: 978-3-642-14922-1
eBook Packages: Computer ScienceComputer Science (R0)