Analyzing the Effects of Data Augmentation on Single and Multimodal Biometrics

  • Mehwish Leghari Department of Information Technology, Quaid-e-Awam University of Engineering, Science and Technology, Nawabshah, Sindh, Pakistan.
  • Shahzad Memon Institute of Information Technology, University of Sindh, Jamshoro, Sindh, Pakistan.
  • Lachman Das Dhomeja Institute of Information Technology, University of Sindh, Jamshoro, Sindh, Pakistan.
  • Akhter Hussain Jalbani Department of Information Technology, Quaid-e-Awam University of Engineering, Science and Technology, Nawabshah, Sindh, Pakistan.

Abstract

Now-a-days, in the field of machine learning the data augmentation techniques are common in use, especially with deep neural networks, where a large amount of data is required to train the network. The effectiveness of the data augmentation technique has been analyzed for many applications; however, it has not been analyzed separately for the multimodal biometrics. This research analyzes the effects of data augmentation on single biometric data and multimodal biometric data. In this research, the features from two biometric modalities: fingerprint and signature, have been fused together at the feature level. The primary motivation for fusing biometric data at feature level is to secure the privacy of the user’s biometric data. The results that have been achieved by using data augmentation are presented in this research. The experimental results for the fingerprint recognition, signature recognition and the feature-level fusion of fingerprint with signature have been presented separately. The results show that the accuracy of the training classifier can be enhanced with data augmentation techniques when the size of real data samples is insufficient. This research study explores that how the effectiveness of data augmentation gradually increases with the number of templates for the fused biometric data by making the number of templates double each time until the classifier achieved the accuracy of 99%.

Published
Jul 1, 2020
How to Cite
LEGHARI, Mehwish et al. Analyzing the Effects of Data Augmentation on Single and Multimodal Biometrics. Mehran University Research Journal of Engineering and Technology, [S.l.], v. 39, n. 3, p. 647 - 656, july 2020. ISSN 2413-7219. Available at: <https://publications.muet.edu.pk/index.php/muetrj/article/view/1707>. Date accessed: 25 sep. 2020. doi: http://dx.doi.org/10.22581/muet1982.2003.19.
Section
Articles
This is an open Access Article published by Mehran University of Engineering and Technolgy, Jamshoro under CCBY 4.0 International License