Abstract
Hand biometrics is globally deployed for automated human identification based on the discriminative geometric characteristics of hand. Advancements in hand biometric technologies are accomplished over several decades. The key objectives of this paper are two-fold. Firstly, it presents a comprehensive study on the state-of-the-art methods based on the hand images collected in an unconstraint environment. Secondly, a pose-invariant hand geometry system is excogitated. The experiments are conducted with the weighted geometric features computed from the fingers. The feature weighted k-nearest neighbor (fwk-NN) classifier is applied on the right- and left-hand images of the 500 subjects of the Bosphorus database for performance evaluation. The classification accuracy of 97% has been achieved for both of the hands using the fwk-NN classifier. Equal error rates (EER) of 5.94% and 6.08% are achieved for the right- and left-hand 500 subjects, respectively.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Jain, A.K., Ross, A., Prabhakar, S.: An introduction to biometric recognition. IEEE Trans. Circuits Syst. Video Technol. 14(1), 4–20 (2004)
Borgia, E.: The internet of things vision: key features, applications, and open issues. Comput. Commun. 54, 1–31 (2014)
Jain, A.K., Nandakumar, K., Ross, A.: 50 years of biometric research: accomplishments, challenges, and opportunities. Pattern Recogn. Lett. 79, 80–105 (2016)
Miller, R.P.: Finger dimension comparison identification system. U.S. Patent No. 3576538 (1971)
Beenau, B.W., Bonalle, D.S., Gray, W.J., Larkin, C., Montgomery, J.L., Saunders, P.D.: Hand Geometry Recognition Biometrics on a Fob. U.S. Patent No. 7886157 B2 (2011)
Kanhangad, V., Kumar, A., Zhang, D.: A unified framework for contactless hand verification. IEEE Trans. Informat. Forensics Secur. 6(3), 1014–1027 (2011)
Dutağaci, H., Sankur, B., Yörük, E.: A comparative analysis of global hand appearance-based person recognition. J. Electron. Imag. 17(1), 011018/1–19 (2008)
Duta, N.: A survey of biometric technology based on hand shape. Pattern Recogn. 42(11), 2797–2806 (2009)
Kang, W., Wu, Q.: Pose-invariant hand shape recognition based on finger geometry. IEEE Trans. Syst. Man Cybernet. Syst. 44(11), 1510–1521 (2014)
Sharma, S., Dubey, S.R., Singh, S.K., Saxena, R., Singh R.K.: Identity verification using shape and geometry of human hands. Expert Syst. Appl. 42(2), 821–832 (2015)
Charfi, N., Trichili, H., Alimi, A.M., Solaiman, B.: Novel hand biometric system using invariant descriptors. In: IEEE International Conference on Soft Computing and Pattern Recognition, pp. 261–266 (2014)
Vivencio, D.P., Hruschka, Jr. E.R., Nicoletti, M.D., Santos, E.B., Galvão, S.D.C.O.: Feature-weighted k-Nearest Neighbor Classifier. IEEE Symposium on Foundations of Computational Intelligence (FOCI), pp. 481–486 (2007)
Yörük, E., Konukoğlu, E., Sankur, B., Darbon, J.: Shape-based hand recognition. IEEE Trans. Image Process. 15(7), 1803–1815 (2006)
Wang, M.H., Chung, Y.K.: Applications of thermal image and extension theory to biometric personal recognition. Expert Syst. Appl. 39(8), 7132–7137 (2012)
Faundez-Zanuy, M., Mekyska, J., Font-Aragonès, X.: A new hand image database simultaneously acquired in visible, near-infrared, and thermal spectrums. Cogn. Comput. 6(2), 230–240 (2014)
Ferrer, M.A., Morales, A., Diaz, A.: An approach to SWIR hyperspectral hand biometrics. Informat. Sci. 268, 3–19 (2014)
Morales, A., Ferrer, M.A., Cappelli, R., Maltoni, D., Fierrez, J., Ortega-Garcia, J.: Synthesis of large-scale hand-shape databases for biometric applications. Pattern Recogn. Lett. 68(1), 183–189 (2015)
Luque-Baena, R.M., Elizondo, D., López-Rubio, E., Palomo, E.J., Watson, T.: Assessment of geometric features for individual identification and verification in biometric hand systems. Expert Syst. Appl. 40(9), 3580–3594 (2013)
Hu, R.X., Jia, W., Zhang, D., Gui, J., Song, L.T.: Hand shape recognition based on coherent distance shape contexts. Pattern Recogn. 45(9), 3348–3359 (2012)
Guo, J.M., Hsia, C.H., Liu, Y.F., Yu, J.C., Chu, M.H., Le, T.N.: Contact-free hand geometry-based identification system. Expert Syst. Appl. 39, 11728–11736 (2012)
Travieso, C.M., Ticay-Rivas, J.R., Briceño, J.C., Pozo-Baños, M., Alonso, J.B.: Hand shape identification on multirange images. Informat. Sci. 275, 45–56 (2014)
El-Sallam, A., Sohel, F., Bennamoun, M.: Robust pose invariant shape-based hand recognition. In: 6th IEEE Conference on Industrial Electronics and Applications, pp. 281–286 (2011)
Hanmandlu, M., Grover, J., Madasu V.K., Vasirkala, S.: Score level fusion offhand based biometrics using T-norms. IEEE, 70–76 (2010)
Acknowledgements
The authors would like to thank Prof. B. Sankur of Bogazici University for providing the hand image database used in this paper.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Bera, A., Bhattacharjee, D., Nasipuri, M. (2019). Pose-Invariant Hand Geometry for Human Identification Using Feature Weighted k-NN Classifier. In: Chandra, P., Giri, D., Li, F., Kar, S., Jana, D. (eds) Information Technology and Applied Mathematics. Advances in Intelligent Systems and Computing, vol 699. Springer, Singapore. https://doi.org/10.1007/978-981-10-7590-2_8
Download citation
DOI: https://doi.org/10.1007/978-981-10-7590-2_8
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-10-7589-6
Online ISBN: 978-981-10-7590-2
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)