Abstract
In this paper we present a unique approach to personal identification which utilized finger surface features as a biometric identifier. Finger surface features are extracted from dense range images of an individual’s hand. The shape index (a curvature-based surface representation) is used to represent the surfaces of the index, middle, and ring fingers of an individual. This representation is used along with a correlation coefficient based matcher to determine similarity. Our experiments make use of data from 223 subjects possessing a 16 week time lapse between collections. We examine the performance of individual finger surfaces in a verification context as well as the performance when using the three finger surfaces in conjunction. We present the results of our experiments, which indicate that this approach performs well for a first-of-its-kind biometric technique.
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
Preview
Unable to display preview. Download preview PDF.
References
Jain, A.K., Ross, A., Pankanti, S.: A Prototype Hand Geometry-Based Verification System. In: Proc. of 2nd Int’l Conference on Audio- and Video-based Biometric Person Authentication (AVBPA), Washington, D.C., pp. 166–171 (1999)
Sanchez-Reillo, R., Sanchez-Avila, C., Gonzalez-Marcos, A.: Biometric Identification through Hand Geometry Measurements. IEEE Trans. on Pattern Analysis and Machine Intelligence 22, 1168–1171 (2000)
Jain, A.K., Duta, N.: Deformable Matching Of Hand Shapes For Verification. In: Proceedings of International Conference on Image Processing, pp. 857–861 (1999)
Lay, Y.L.: Hand Shape Recognition. Optics and Laser Technology 32, 1–5 (2000)
Woodard, D.L.: Exploiting Finger Surface as a Biometric Identifier. PhD thesis, The University of Notre Dame, Notre Dame, IN 46556, USA (2004)
Konica Minolta Website: http://konicaminolta.com (Accessed 2004)
Kovač, J., Peer, P., Solina, F.: Human Skin Colour Clustering for Face Detection. In: Zajc, B. (ed.) EUROCON 2003 - International Conference on Computer as a Tool, Ljubljana, Slovenia (2003)
Flynn, P.J., Jain, A.K.: On reliable curvature estimation. In: Proc. IEEE Conf. Computer Vision and Pattern Recognition, vol. 89, pp. 110–116 (1989)
Koenderink, J.J., van Doorn, A.J.: Surface shape and curvature scales. Image and Vision Computing 10, 557–564 (1992)
Dorai, C., Jain, A.K.: COSMOS-A Representation Scheme for Free-Form Surfaces. In: International Conference on Computer Vision, pp. 1024–1029 (1995)
Dorai, C., Jain, A.K.: COSMOS-A Representation Scheme for 3D Free-Form Objects. IEEE Trans. on Pattern Analysis and Machine Intelligence 19, 1115–1130 (1997)
Ross, A., Jain, A.K.: Information Fusion in Biometrics. Pattern Recognition Letters 24, 2115–2125 (2003)
Hong, L., Jain, A.K., Pankanti, S.: Can Multibiometrics Improve Performance. Technical Report MSU-CSE-99-39, Department of Computer Science, Michigan State University, East Lansing, Michigan (1999)
Kittler, J., Hatel, M., Duin, R.P.W., Matasm, J.: On Combining Classifiers. IEEE Trans. on Pattern Analysis and Machine Intelligence 20, 226–239 (1998)
Phillips, P.J., Moon, H., Rizvi, S.A., Rauss, P.J.: The FERET Evaluation Methodology for Face-Recognition Algorithms. IEEE Transactions on Pattern Analysis and Machine Intelligence 22, 1090–1104 (2000)
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
Woodard, D.L., Flynn, P.J. (2005). Identity Verification Utilizing Finger Surface Features. In: Kanade, T., Jain, A., Ratha, N.K. (eds) Audio- and Video-Based Biometric Person Authentication. AVBPA 2005. Lecture Notes in Computer Science, vol 3546. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11527923_56
Download citation
DOI: https://doi.org/10.1007/11527923_56
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-27887-0
Online ISBN: 978-3-540-31638-1
eBook Packages: Computer ScienceComputer Science (R0)