Face recognition using DT-CWT and LBP features

Biometric technology is considered as more effective technology for identification and recognition of individuals in most secure environments. Face recognition is a technique based on physiological biometric characteristics. In this paper, we propose Face Recognition using DT-CWT and LBP Features (FRDL) for different databases. The original face image is resized to uniform dimensions of 2p × 2q. The five levels Dual-Tree Complex Wavelet Transform (DT-CWT) is applied on face image to obtain DT-CWT coefficients. The matrix of DT-CWT coefficients is segmented in to 3×3 matrixes. The Local Binary Pattern (LBP) algorithm is applied on each 3×3 matrix to get final features. The Euclidean Distance (ED) is used to compare features of test face image with data base images. It is observed that the values of False Rejection Rate (FRR), False Acceptance Rate (FAR) and Total Success Rate (TSR) are better in the proposed model compare to existing method.

[1]  Oksam Chae,et al.  Robust Facial Expression Recognition Based on Local Directional Pattern , 2010 .

[2]  Masashi Nishiyama,et al.  Face recognition using the classified appearance-based quotient image , 2006, 7th International Conference on Automatic Face and Gesture Recognition (FGR06).

[3]  K. Jaya Priya.  Dual Tree Complex Wavelet Transform based Face Recognition with Single View , 2010 .

[4]  Rerkchai Fooprateepsiri,et al.  Facial Recognition using Hausdorff- Shape- Radon Transform , 2009, J. Digit. Content Technol. its Appl..

[5]  Matti Pietikäinen,et al.  Multiresolution Gray-Scale and Rotation Invariant Texture Classification with Local Binary Patterns , 2002, IEEE Trans. Pattern Anal. Mach. Intell..

[6]  Richard Baraniuk,et al.  The Dual-tree Complex Wavelet Transform , 2007 .

[7]  Mauridhi Hery Purnomo,et al.  Appearance Global and Local Structure Fusion for Face Image Recognition , 2011 .

[8]  Vitomir Struc,et al.  Gabor-Based Kernel Partial-Least-Squares Discrimination Features for Face Recognition , 2009, Informatica.

[9]  Yongsheng Gao,et al.  Establishing point correspondence using multidirectional binary pattern for face recognition , 2008, 2008 19th International Conference on Pattern Recognition.

[10]  Sudeep D. Thepade,et al.  Iris recognition using texture features extracted from Walshlet pyramid , 2011, ICWET.

[11]  K Ramesha,et al.  Dual Transform based Feature Extraction for Face Recognition , 2011 .

[12]  Driss Aboutajdine,et al.  Local Steerable Pyramid Binary Pattern Sequence LSPBPS for Face Recognition Method , 2009 .

[13]  Mariko Nakano-Miyatake,et al.  A Face Recognition Algorithm using Eigenphases and Histogram Equalization , .

[14]  Sanjay N. Talbar,et al.  Independent Component Analysis of Edge Information for Face Recognition , 2013 .