Hybrid feature extraction and LLTSA-based dimension reduction for vein pattern recognition

Abstract

ABSTRACTIn information and security, the personal identification of individuals becomes much more important. For improving security, several biometric recognition techniques are implemented. However, in finger vein recognition, it faces the critical problem of fake finger vein images, security and less accuracy. To conquer this problem, Hybrid Feature Extraction with Linear Local Tangent Space Alignment-based dimension reduction and Support Vector Machine classifier (HFE–LLTSA–SVM) is proposed. In this hybrid, FE is considered as the combination of histogram of oriented gradients (HOG), grey-level co-occurrence matrix (GLCM), stationary wavelet transform (SWT), and local binary pattern (LBP) for extracting the hybrid feature. LLTSA perform dimension reduction in the outputs of HFE from HOG, GLCM, and LBP. Furthermore, SVM is used for classification which gives authentication based on error-correcting code. Finally, the performance parameters were calculated and the proposed method achieved better accuracy of 99.75%, when compared with existing methods.KEYWORDS: Grey-level co-occurrence matrixhistogram of oriented gradientlocal binary patternstationary wavelet transformsupport vector machine Disclosure statementNo potential conflict of interest was reported by the author(s).Additional informationNotes on contributorsP. GopinathDr P. Gopinath is working as an Assistant Professor in the department of Electronics and Communication Engineering at Sengunthar Engineering College, Tiruchengode. He obtained his Ph. D in Digital Image Processing from Anna University Chennai in 2023. M.E. (Applied Electronics) from Anna University Chennai in 2011. B.E. (Electronics and Communication Engineering) from Anna University Chennai in 2008.He has a 13 years of teaching experience. His research interest includes Digital Image processing, Signal processing, Biometrics, Machine learning, and Artificial Intelligence. He has published more than 12 research article and 2 patent.R. ShivakumarDr R. Shivakumar is working as a Professor in Department of Electrical and Electronics Engineering at Sona College of Technology, Salem. He obtained his Ph. D in Electrical Engineering from Anna University Chennai in November 2012.M.E. (Power System Engg) -First class with Distinction in 1998 from Annamalai University, Chidambaram. B.E. (Electrical and Electronics Engineering) with I Class in 1997, from Shanmugha College of Engineering, Tanjore, Bharadhidasan University. His research interest includes Power System Stability and Control, Bio Inspired Optimization algorithms, Renewable energy conversion systems, and Digital Technology applications in Power Engineering. He has published more than 40 research article and 60 International and National Conference Papers. He won BEST RESEARCHER Award for academic contribution in Electrical and Electronics Engineering specialization under National Faculty Award 2021-2022 awarded by Novel Research Academy, Puducherry, India on 4.5.2022.