This paper focuses on hand biometrics applied to images acquired from a mobile device. The system offers the possibility of identifying individuals based on features extracted from hand pictures obtained with a low-quality camera embedded on a mobile device. Furthermore, the acquisitions have been carried out regardless illumination control, orientation, distance to camera, and similar aspects. In addition, the whole system has been tested with an owned database. Finally, the results obtained (6.0% ± 0.2) and the algorithm structure are both promising in relation to a posterior mobile implementation.
This is a preview of subscription content, log in to check access.
Buy single article
Instant access to the full article PDF.
Price includes VAT for USA
Subscribe to journal
Immediate online access to all issues from 2019. Subscription will auto renew annually.
This is the net price. Taxes to be calculated in checkout.
Bolle R., Pankanti S.: Biometrics, Personal Identification in Networked Society: Personal Identification in Networked Society. Kluwer Academic Publishers, Norewell, MA (1998)
Arif, M., Brouard, T., Vincent, N.: Personal identification and verification by hand recognition. In: IEEE International Conference on Engineering of Intelligent Systems, pp. 1–6 (2006)
Su C.L.: Overlapped finger geometry signal processing and finger shape comparisons for person identification. Informatica 18, 447–456 (2007)
Kang B.J., Park K.R.: Multimodal biometric authentication based on the fusion of finger vein and finger geometry. Opt. Eng. 48, 090501 (2009)
Malassiotis S., Aifanti N., Strintzis M.: Personal authentication using 3-d finger geometry. IEEE Trans. Inf. Forensics Secur. 1, 12–21 (2006)
Yoruk E., Konukoglu E., Sankur B., Darbon J.: Shape-based hand recognition. IEEE Trans. Image Process. 15, 1803–1815 (2006)
de Santos Sierra, A., Casanova, J., Avila, C., Vera, V.: Silhouette-based hand recognition on mobile devices. In: 43rd Annual 2009 International Carnahan Conference on Security Technology, pp. 160–166 (2009)
Morales, A., Ferrer, M., Alonso, J., Travieso, C.: Comparing infrared and visible illumination for contactless hand based biometric scheme. In:42nd Annual IEEE International Carnahan Conference on Security Technology (ICCST), pp. 191–197 (2008)
Cortes, C., Vapnik, V.: Support-vector networks. In: Machine Learning, Springer, New York, pp. 273–297 (1995)
Cristianini N., Shawe-Taylor J.: An introduction to support vector machines: and other kernel-based learning methods. 1st edn. Cambridge University Press, Cambridge (2000)
Shahin, M., Badawi, A., Rasmy, M.: A multimodal hand vein, hand geometry, and fingerprint prototype design for high security biometrics. In: Cairo International Biomedical Engineering Conference (CIBEC), pp. 1–6 (2008)
Alpert, S., Galun, M., Basri, R., Brandt, A.: Image segmentation by probabilistic bottom-up aggregation and cue integration. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 1–8 (2007)
Son, T., Mita, S., Takeuchi, A.: Road detection using segmentation by weighted aggregation based on visual information and a posteriori probability of road regions. In: IEEE International Conference on Systems, Man and Cybernetics (SMC), pp. 3018–3025 (2008)
Hunter R.S.: Photoelectric color difference meter. J. Opt. Soc. Am. 48, 985–993 (1958)
Gonzalez R.C., Woods R.E.: Digital Image Processing. Addison-Wesley Longman Publishing Co., Inc., Boston, MA (2001)
About this article
Cite this article
de Santos Sierra, A., Sánchez-Ávila, C., Mendaza Ormaza, A. et al. An approach to hand biometrics in mobile devices. SIViP 5, 469 (2011). https://doi.org/10.1007/s11760-011-0250-8
- Contact-less hand biometrics
- Mobile devices
- Support vector machines