A fingerprint capture consists of touching or rolling a finger onto a rigid sensing surface. During this act, the elastic skin of the finger deforms. The quantity and direction of the pressure applied by the user, the skin conditions, and the projection of an irregular 3D object (the finger) onto a 2D flat plane introduce distortions, noise, and inconsistencies on the captured fingerprint image. Due to these negative effects, the representation of the same fingerprint changes every time the finger is placed on the sensor platen, increasing the complexity of the fingerprint matching and representing a negative influence on the system performance. Recently, a new approach to capture fingerprints has been proposed. This approach, referred to as touchless or contactless fingerprinting, tries to overcome the above-cited problems. Because of the lack of contact between the finger and any rigid surface, the skin does not deform during the capture and the repeatability of the measure is quiet ensured. However, this technology introduces new challenges. Finger positioning, illumination, image contrast adjustment, data format compatibility, and user convenience are key in the design and development of touchless fingerprint systems. In addition, vulnerability to spoofing attacks of some touchless fingerprint systems must be addressed.
- Optical Coherence Tomography
- Cylindrical Model
- Minutia Point
- Liveness Detection
- Valley Structure
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
This is a preview of subscription content, access via your institution.
Unable to display preview. Download preview PDF.
E. German, Latent Print Examination, http://www.onin.com/fp, 2007.
Matsumoto, T., Matsumoto, H., Yamada, K. and Hoshino, S., Impact of Artificial Gummy Fingers on Fingerprint Systems. Proceedings SPIE, Vol. 4677, pp. 275–289, San Jose, USA, Feb 2002.
Bolle, R.M., Connell, J.H. and Ratha, N.K., Biometric Perils and Patches. Pattern Recognition, vol. 25, no. 12, pp. 2727–2738.
Matsumoto, T., Matsumoto, H., Yamada, K. and Hoshino, S., Impact of Artificial Gummy Fingers on Fingerprint Systems. Proceedings on SPIE, Vol. 4677, pp. 275–289, San Jose, USA, Feb 2002.
Testimony of Jim Williams Director in US-VISIT Program, Department of Homeland Security, Before The Senate Appropriations Subcommittee on Homeland Security, January 25, 2006, http://appropriations.senate.gov/hearmarkups/JWTestimonyFINAL.pdf.
Parziale, G., Touchless Fingeprinting Technology, a chapter in Advances in Biometrics: Sensors, Systems and Algorithms, Eds. by Nalini K. Ratha and Venu Govundaju, Springer-Verlag Ltd, Berlin, Dec 2007.
Elli, A., Understanding the Color of Human Skin. Proceedings of the 2001 SPIE conference on Human Vision and Electronic Imaging VI, SPIE Vol. 4299, pp. 243–251.
Song, Y., Lee, C. and Kim, J., A New Scheme for Touchless Fingerprint Recognition System. Proceedings of 2004 International Symposium on Intelligent Signal Processing and Communication Systems, pp. 524–527.
Krzysztof M., Preda M. and Axel M., Dynamic Threshold Using Polynomial Surface Regression with Application to The Binarization of Fingerprints. Proceedings of SPIE on Biometric Technology for Human Identification, Orlando, USA, pp. 94–104, 2005.
Lee, C., Lee, S. and Kim, J., A Study of Touchless Fingerprint Recognition System. Springer, New York, Vol. 4109, pp. 358–365, 2006.
Sano, E., Maeda, T., Nakamura, T., Shikai, M., Sakata, K., Matsushita, M. and Sasakawa, K., Fingerprint Authentication Device Based on Optical Characteristics Inside a Finger. In Proceedings of the 2006 Conference on Computer Vision and Pattern Recognition Workshop (June 17–22, 2006). CVPRW. IEEE Computer Society, Washington, DC, 27.
Shiratsuki, A., Sano, E., Shikai, M., Nakashima, T., Takashima, T., Ohmi, M. and Haruna, M., Novel Optical Fingerprint Sensor Utilizing Optical Characteristics of Skin Tissue Under Fingerprints. International Society for Optical Engineering, Proceedings SPIE, Vol. 5686, pp. 80–87, 2006.
TBS Touchless Fingerprint Imaging, http://www/tbsinc.com.
Parziale, G., Diaz-Santana, E. and Hauke, R., The Surround Imager: A Multi-Camera Touchless Device to Acquire 3D Rolled-Equivalent Fingerprints. Proceedings of IAPR International Conference on Biometrics (ICB), pp. 244–250, Hong Kong, China.
Hauke, R., Parziale, G. and Paar, G., Method and Arrangement for Optical Recording of Biometric Data. Patent. PCT/DE2004/002026, 2004.
Proceedings of IEEE Conference on computer Vision and Pattern Recognition, Florida, USA, 1086, pp. 364–374.
Sonka, M., Hlavac, V. and Boyle, R., Image Processing, Analysis, and Machine Vision. Second Edition, Brooks/Cole Publishing, USA. 1999.
Gruen, A. and Huang, T.A. (Eds.), Calibration and Orientation of Cameras in Computer Vision. Springer-Verlag, Berlin, 2001
Hartley, R. and Zisserman, A., Multiple View Geometry in Computer Vision. Cambridge University Press, UK, 2003.
Flashscan 3D Touchless Fingerprint Sensor, http://www.flashscan3d.com/.
Fatehpuria, A., Lau, D.L., and Hassebrook, L.G., Acquiring a 2-D Rolled Equivalent Fingerprint Image from a Non-Contact 3-D Finger Scan. Biometric Technology for Human Identification III, edited by Patrick J. Flynn, Sharath Pankanti, SPIE Defense and Security Symposium, Orlando, Florida, Vol. 6202, pp. 62020C-1 to 62020C-8, 2006.
Ross, A. and Jain, A.K., Biometric Sensor Interoperability: A Case Study in Fingerprints, in Proceedings of ECCV International Workshop on Biometric Authentication (BioAW), Prague, Czech Republic, May 2004, vol. LNCS 3087, pp. 134–145, Springer, New York.
Bolle, R.M., Ratha, N.K., Senior, A. and Pankanti, S., Minutia Template Exchange Format, in Proc. of IEEE Workshop on Automatic Identification Advanced Technologies, 1999, pp. 74–77.
Podio, F.L., Dunn, J. S., Reinert, L., Tilton, C.J., O’Gorman, L., Collier, P., Jerde, B. and Wirtz, M., Common Biometric Exchange File Format (CBEFF), Technical Report NISTIR 6529, NIST, January 2001.
Snyde, J. P., Flattening the Earth: Two Thousand Years of Map Projections, The University of Chicago Press, Chicago, 1993.
Yang, O., Tobler, W. Snyder, J. and Yang, Q. H., Map Projection Transformation, Taylor and Francis, Abinsdon, 2000.
From FLand: map projection methods, http://gpscycling.net/fland/map/projection.html
Jain, A.K., Hong, L. and Bolle, R., On-line Fingerprint Verification, IEEE Transactions on Pattern Analysis and Machine Intel ligence, vol. 19, no. 4, pp. 302–314, April 1997.
Tips for Rolling Fingerprints, http://apps.mentoring.org/safetynet/fingtips.pdf.
Gonzalez R.C. and Woods, R.E., Digital Image Processing, Prentice Hall, Upper Saddle River, NJ, 2002.
Chen, Y., Dass, S. C. and Jain, A. K., Fingerprint Quality Indices for Predicting Authentication Performance, in Proc. International Conference on Audio- and Video-Based Biometric Person Authentication, pp. 160–170, 2005.
Neurotechnologija Verifinger SDK,, http://www.neurotechnologija.com/vfsdk.html.
Putte, T. and Keuning, J., Biometrical Fingerprint Recognition: Dont Get Your Fingers Burned. Proc. IFIP TC8/WG8.8, 4th Working Conf. Smart Card Research and Adv. App. pp. 289–303, 2000.
Diaz-Santana, E. and Parziale, G., Liveness Detection Method. EP1872719, 2006.
Editors and Affiliations
Rights and permissions
© 2009 Springer-Verlag London Limited
About this chapter
Cite this chapter
Parziale, G., Chen, Y. (2009). Advanced Technologies for Touchless Fingerprint Recognition. In: Tistarelli, M., Li, S.Z., Chellappa, R. (eds) Handbook of Remote Biometrics. Advances in Pattern Recognition. Springer, London. https://doi.org/10.1007/978-1-84882-385-3_4
Publisher Name: Springer, London
Print ISBN: 978-1-84882-384-6
Online ISBN: 978-1-84882-385-3
eBook Packages: Computer ScienceComputer Science (R0)