Local appearance-based face recognition using adaptive directional wavelet transform

Abstract The latest research has shown that adaptive directional wavelet transform can constitute edges and textures in images efficiently due to the adaptive directional selectivity. This paper is primarily focused on the application of adaptive directional wavelet transform in conjunction with linear discriminant analysis (LDA) for capturing the discriminant directional multiresolution facial features. The intention of this paper is to explore the efficacy of adaptive directional wavelet transform in facial feature extraction and to offer a stepping stone for further research in this direction. The proposed approach is compared with existing subspace and local descriptor feature extraction methods. A performance comparison is also demonstrated with existing non-adaptive multiresolution analysis methods such as discrete wavelet transform (DWT), Gabor wavelet transform (GWT), curvelets, ridgelets, contourlets, and local Gabor binary pattern. Evaluation of the proposed approach on famous databases such as ORL, Essex Grimace, Yale, and Sterling face convinces the effectiveness of the adaptive directional wavelet transform based subspace features.

[1]  Wen Gao,et al.  Local Gabor binary pattern histogram sequence (LGBPHS): a novel non-statistical model for face representation and recognition , 2005, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1.

[2]  Chengjun Liu,et al.  Gabor-based kernel PCA with fractional power polynomial models for face recognition , 2004, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[3]  Konstantinos N. Plataniotis,et al.  Face recognition using kernel direct discriminant analysis algorithms , 2003, IEEE Trans. Neural Networks.

[4]  Pong C. Yuen,et al.  Human face recognition using PCA on wavelet subband , 2000, J. Electronic Imaging.

[5]  Jelena Kovacevic,et al.  Wavelet families of increasing order in arbitrary dimensions , 2000, IEEE Trans. Image Process..

[6]  M. Turk,et al.  Eigenfaces for Recognition , 1991, Journal of Cognitive Neuroscience.

[7]  Ong Thian Song,et al.  An efficient fingerprint verification system using integrated wavelet and Fourier–Mellin invariant transform , 2004 .

[8]  David J. Kriegman,et al.  Eigenfaces vs. Fisherfaces: Recognition Using Class Specific Linear Projection , 1996, ECCV.

[9]  Shutao Li,et al.  Face recognition using Weber local descriptors , 2013, Neurocomputing.

[10]  Bernhard Schölkopf,et al.  Kernel Principal Component Analysis , 1997, ICANN.

[11]  Minh N. Do,et al.  Ieee Transactions on Image Processing the Contourlet Transform: an Efficient Directional Multiresolution Image Representation , 2022 .

[12]  Dattatray V. Jadhav,et al.  Feature extraction using Radon and wavelet transforms with application to face recognition , 2009, Neurocomputing.

[13]  R. S. Holambe,et al.  Enhancing Face Recognition Performance using Triplet Half Band Wavelet Filter Bank , 2016 .

[14]  Eero P. Simoncelli.  A rotation invariant pattern signature , 1996, Proceedings of 3rd IEEE International Conference on Image Processing.

[15]  Marian Stewart Bartlett,et al.  Independent component representations for face recognition , 1998, Electronic Imaging.

[16]  Melvyn L. Smith,et al.  Face recognition in 2D and 2.5D using ridgelets and photometric stereo , 2012, Pattern Recognit..

[17]  Minh N. Do,et al.  The finite ridgelet transform for image representation , 2003, IEEE Trans. Image Process..

[18]  Wim Sweldens,et al.  The lifting scheme: a construction of second generation wavelets , 1998 .

[19]  Laurent Demanet,et al.  Fast Discrete Curvelet Transforms , 2006, Multiscale Model. Simul..

[20]  Feng Chen,et al.  Facial expression recognition and its application based on curvelet transform and PSO-SVM , 2013 .

[21]  Driss Aboutajdine,et al.  Local appearance based face recognition method using block based steerable pyramid transform , 2011, Signal Process..

[22]  Matti Pietikäinen,et al.  IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2009, TPAMI-2008-09-0620 1 WLD: A Robust Local Image Descriptor , 2022 .

[23]  Bernd Girod,et al.  Direction-Adaptive Discrete Wavelet Transform for Image Compression , 2007, IEEE Transactions on Image Processing.

[24]  Zhenghua Zhou,et al.  Pose and illumination variable face recognition via sparse representation and illumination dictionary , 2016, Knowl. Based Syst..

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

[26]  Jiri Matas,et al.  Support vector machines for face authentication , 2002, Image Vis. Comput..

[27]  Feng Wu,et al.  Adaptive Directional Lifting-Based Wavelet Transform for Image Coding , 2007, IEEE Transactions on Image Processing.

[28]  Jun Wang,et al.  Non-uniform patch based face recognition via 2D-DWT , 2015, Image Vis. Comput..

[29]  Chengjun Liu,et al.  Gabor feature based classification using the enhanced fisher linear discriminant model for face recognition , 2002, IEEE Trans. Image Process..

[30]  Ahmed Bouridane,et al.  Contourlet-Based Feature Extraction with PCA for Face Recognition , 2008, 2008 NASA/ESA Conference on Adaptive Hardware and Systems.

[31]  A. Vinay,et al.  Face Recognition Using Gabor Wavelet Features with PCA and KPCA - A Comparative Study☆ , 2015 .

[32]  Jen-Tzung Chien,et al.  Discriminant Waveletfaces and Nearest Feature Classifiers for Face Recognition , 2002, IEEE Trans. Pattern Anal. Mach. Intell..

[33]  Q. M. Jonathan Wu,et al.  Curvelet based face recognition via dimension reduction , 2009, Signal Process..

[34]  R. S. Holambe,et al.  Face recognition using LDA based generalized half band polynomial wavelet filter bank , 2016, 2016 International Conference on Electrical, Electronics, and Optimization Techniques (ICEEOT).

[35]  Hui Han,et al.  Discriminant sparse local spline embedding with application to face recognition , 2015, Knowl. Based Syst..

[36]  Jun Wang,et al.  Face recognition based on pixel-level and feature-level fusion of the top-level's wavelet sub-bands , 2015, Inf. Fusion.

[37]  Arian Maleki,et al.  Rate-Distortion Analysis of Directional Wavelets , 2012, IEEE Transactions on Image Processing.

[38]  Sharath Pankanti,et al.  Biometrics: a tool for information security , 2006, IEEE Transactions on Information Forensics and Security.

[39]  Matti Pietikäinen,et al.  Face Description with Local Binary Patterns: Application to Face Recognition , 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.