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An Ensemble Based Hand Vein Pattern Authentication System

M. Rajalakshmi*

Department of Information Technology, SRM University, Chennai -603203
2, 3, 4, 5, 6 Department of Electrical and Electronics Engineering, SSN College of Engineering, Chennai -603110

*Corresponding Author: M. Rajalakshmi. Email: email

Computer Modeling in Engineering & Sciences 2018, 114(2), 209-220.


Amongst several biometric traits, Vein pattern biometric has drawn much attention among researchers and diverse users. It gains its importance due to its difficulty in reproduction and inherent security advantages. Many research papers have dealt with the topic of new generation biometric solutions such as iris and vein biometrics. However, most implementations have been based on small datasets due to the difficulties in obtaining samples. In this paper, a deeper study has been conducted on previously suggested methods based on Convolutional Neural Networks (CNN) using a larger dataset. Also, modifications are suggested for implementation using ensemble methods. Ensembles were used to reduce training time and cost by training multiple weak classifiers instead of a single, strong classifier. Classifiers used were CNN, Random Forest and Logistic Regression. An inexpensive and robust data acquisition system was also developed for obtaining the dataset. The obtained result shows an improved accuracy of 96.77% using ensemble method instead of dealing with a single classifier.


Cite This Article

APA Style
Rajalakshmi, M. (2018). An ensemble based hand vein pattern authentication system. Computer Modeling in Engineering & Sciences, 114(2), 209-220.
Vancouver Style
Rajalakshmi M. An ensemble based hand vein pattern authentication system. Comput Model Eng Sci. 2018;114(2):209-220
IEEE Style
M. Rajalakshmi, "An Ensemble Based Hand Vein Pattern Authentication System," Comput. Model. Eng. Sci., vol. 114, no. 2, pp. 209-220. 2018.

cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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