International Journal of Nonlinear Analysis and Applications
Hand vein recognition with rotation feature matching based on fuzzy algorithm
Document Type : Research Paper
Authors
1 Business Information Technology Department, Business Informatics College, University of Information Technology and Communications, Baghdad, Iraq.
2 Bioinformatics Department, BioMedical Informatics College, University of Information Technology and Communications, Baghdad, Iraq.
Abstract
The Bodily motion or emotion, which can be obtained for example from a hand or a face, originates gestures. Every individual has a unique pattern of dorsal hand veins. The vein pattern's orientation changes when one rotates their hand in a particular direction. This study focused on hand-gesture recognition using dorsal hand veins. The aim of this work is a novel technique to track and recognizing hand vein rotation using fuzzy neural network, and the change in orientation was considered as a gesture and measured. The algorithms were tested over various rotations ranging from $-45^{\circ}$ to $+45^{\circ}$. We successfully detected various rotations in both clockwise and anti-clockwise directions, achieving $93\%$ accuracy and a reasonable time execution. This problem can be solved because a person can steer a car wheel merely by rotating his/her hand. An infrared camera captured the rotation of hand veins, so car wheel steering was unnecessary.
Keywords
J. Comput. Appl. 50(7) (2012) 38–44.
[2] H. Al Azawee, S. Husien and M.A.M. Yunus, Encryption function on artificial neural network, Neural Comput.
Appl. 27(8) (2016) 2601–2604.
[3] M.A. Al-Sharqi and H.S. Hasan, Fuzzy control algorithm for estimation and interaction of dynamic arm motion,
Recent Adv. Comput. Sci. Commun. 13(1) (2019) 99–104.
[4] P. Arora, G. Chaudhary and S. Srivastava, Exploiting oriented gradient histogram for dorsal vein recognition,
2019 12th Int. Conf. Contemp. Comput. IC3 2019, (2019) 1–4.
[5] H. Badi, Recent methods in vision-based hand gesture recognition, Int. J. Data Sci. Anal. 1(2) (2016) 77–87.
[6] A.S. Bhosale and M.R. Jadhav, Dorsal hand vein pattern recognition system based on neural network, Proc. Int.
Conf. Electron. Commun. Aerosp. Tech. 2017 (2017) 52–55.
[7] V. Dixit and A. Agrawal, Real time hand detection & tracking for dynamic gesture recognition, Int. J. Intell. Syst.
Appl. 7(8) (2015) 38–44.
[8] R.M. Gurav, Vision based hand gesture recognition with Haar classifier and AdaBoost algorithm, Int. J. Lat.
Trend. Engin.eering and Tech. 5(2) (2015) 155–160.
[9] C. Kauba and A. Uhl, Shedding light on the veins-reflected light or transillumination in hand-vein recognition,
Proc. -2018 Int. Conf. Biometrics, ICB 2018 (2018) 283–290.
[10] A. Lics´ar and T. Szir´anyi, Hand gesture recognition in camera-projector system, Lect. Notes Comput. Sci. (including Subser. Lect. Notes Artif. Intell. Lect. Notes Bioinformatics), 3058 (2004) 83–93.
[11] K.C. Lim, S.H. Sin, C.W. Lee, W.K. Chin, J. Lin, K. Nguyen, Q.H. Nguyen, B.P. Nguyen and M. Chua, Videobased skeletal feature extraction for hand gesture recognition, ACM Int. Conf. Proceeding Ser. (2020) 108–112.
[12] G.R.S. Murthy and R.S. Jadon, Hand gesture recognition using neural networks, 2010 IEEE 2nd Int. Adv. Comput.
Conf. IACC 2010, no. March 2015, (2010) 134–138.
[13] H. Qin, M.A. El Yacoubi, J. Lin and B. Liu, An iterative deep neural network for hand-vein verification, IEEE
Access 7 (2019) 34823–34837.
[14] T. Saini and S. Sivani, Real time vision hand gesture recognition based media control via LAN & Wireless hardware
control, Int. J. Multidiscip. Educ. Res. 3 (2013) 3129–3133.
[15] R.P. Sharma and G.K. Verma, Human computer interaction using hand gesture, Procedia Comput. Sci. 54 (2015)
721–727.
[16] S.M. Shitole, S.B. Patil and S.P. Narote, Dynamic hand gesture recognition using PCA, Pruning and ANN, Int.
J. Comput. Appl. 74(2) (2013) 24–29.
[17] K. Vasagiri and S.R. Parvata, Dorsal hand vein biometric authentication using complex Walsh transform, Proc.
2016 2nd Int. Conf. Appl. Theor. Comput. Commun. Technol. iCATccT 2016, (2017) 533–537.
[18] W. Wu, S.J. Elliott, S. Lin, S. Sun and Y. Tang, Review of palm vein recognition, IET Biomet. 9(1) (2020) 1–10.[19] J. Wu, L. Wang, G. Yang, L. Senhadji, L. Luo and H. Shu, Sliding conjugate symmetric sequency-ordered complex
hadamard transform: Fast algorithm and applications, IEEE Trans. Circuits Syst. I Regul. Pap. 59(6) (2012)
1321–1334.
[20] L. Yang, J. Chen and W. Zhu, Dynamic hand gesture recognition based on a leap, Sensors 20(7) (2020) 1–17.
[21] H. Zhou and T.S. Huang, Tracking articulated hand motion with eigen dynamics analysis, Proc. IEEE Int. Conf.
Comput. Vis. 2(Iccv) (2003) 1102–1109.
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Volume 12, Special Issue
December 2021Pages 951-958
- Receive Date: 06 June 2021
- Revise Date: 29 July 2021
- Accept Date: 21 August 2021