Abstract
A new approach for personal identification using hand geometry based upon geometrical and shape features is presented. We propose a new pegless hand geometry verification system where the users are free to put their hand in arbitrary fashion. A Linear Discirminant Analysis if applied to the raw data in order to perform a best clustering of the feature space. The combination of three different neural network classifiers (unsupervised SOM, supervised SOM and LVQ) gives 0.35% FAR and 0.15% FRR. The method has been tested on a large size database of 1400 images for training and 1400 for test from 280 individuals suitable for medium and low security applications.
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Jain, A.K., Ross, A., Prabhakar, S.: An Introduction to Biometric Recognition. IEEE Trans. on Circuits and Systems for Video Technology 14(1), 4–20 (2004)
Sanchez-Reillo, R., Sanchez-Avila, C., Gonzalez-Marcos, A.: Biometric Identification through Hand Geometry Measurements. IEEE Trans. on Pattern Analysis and Machine Recognition 22(10), 1169–1171 (2000)
Kumar, A., Wong, D.C.M., Shen, H.C., Jain, A.K.: Personal Verification using Palmprint and Hand Geometry Biometrics. In: Proceedings of the fourth International Conference on audio- and video-based biometric person authentication (2003)
Jain, A.K., Ross, A., Pankanti, S.: A Prototype Hand Geometry-based Verification System. In: Proc. of the 2nd International Conference on Audio- and Video-based Biometric Person Authentication, pp. 166–171 (1999)
http://visgraph.cs.ust.hk/biometrics/Visgraph_web/index.html
Bulatov, Y., Jambawalikar, S., Kumar, P., Sethia, S.: Hand Recognition Using Geometric Classifiers. In: Zhang, D., Jain, A.K. (eds.) ICBA 2004. LNCS, vol. 3072, pp. 753–759. Springer, Heidelberg (2004)
Jain, A.K., Duta, N.: Deformable matching of hand shapes for verification. In: Proceedings of International Conference on Image Processing (1999)
Oden, C., Ercil, A., Kirmizita, H., Buke, B.: Hand recognition using implicit polynomials and geometric feature. In: Bigun, J., Smeraldi, F. (eds.) AVBPA 2001. LNCS, vol. 2091, pp. 336–341. Springer, Heidelberg (2001)
http://www.eng.buffalo.edu/~ssc5/research/papers/biometric_hardening.pdf
Wong, A.L.N., Shi, P.: Peg-Free Hand geometry Recognition Using Hierarchical Geometry and Shape Matching. In: IAPR Workshop on Machine Vision Applications, pp. 281–284 (2002)
Otsu, N.: A threshold selection method from grey-scale histogram. IEEE Trans. Syst., Man, Cybern. 8, 62–66 (1978)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2005 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Martínez, F., Orrite, C., Herrero, E. (2005). Biometric Hand Recognition Using Neural Networks. In: Cabestany, J., Prieto, A., Sandoval, F. (eds) Computational Intelligence and Bioinspired Systems. IWANN 2005. Lecture Notes in Computer Science, vol 3512. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11494669_143
Download citation
DOI: https://doi.org/10.1007/11494669_143
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-26208-4
Online ISBN: 978-3-540-32106-4
eBook Packages: Computer ScienceComputer Science (R0)