Histogram Sequence of Local Gabor Binary Pattern for Face Description and Identification

In this paper, a method for face description and recognition is proposed, which extracts the histogram sequence of local Gabor binary patterns (HSLGBP) from the magnitudes of Gabor coefficients. Since Gabor feature is robust to illumination and expression variations and has been successfully used in face recognition area. First, the proposed method decomposes the normalized face image by convolving the face image with multi-scale and multi-orientation Gabor filters to extract their corresponding Gabor magnitude maps (GMMs). Then, the local binary patterns (LBP) operates on each GMM to extract the local neighbor pattern. Finally, the input face image is described by the histogram sequence extracted from all these region patterns. The proposed method is robust to illumination, expression and misalignment by combing the Gabor transform, LBP and spatial histogram. In addition, this face modeling method does not need the training set for statistic learning, thus it avoids the generalizability problem. Moreover, how to combine the statistic method in the stage of classification and propose statistic Fisher weight HSLGBP matching method are discussed. The results compared with the published results on FERET face database of changing illumination, expression and aging verify the validity of the proposed method.

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

[2]  Wen Gao,et al.  Multi-resolution Histograms of Local Variation Patterns (MHLVP) for Robust Face Recognition , 2005, AVBPA.

[3]  B. K. Julsing,et al.  Face Recognition with Local Binary Patterns , 2012 .

[4]  Norbert Krüger,et al.  Face Recognition by Elastic Bunch Graph Matching , 1997, CAIP.

[5]  Aleix M. Martinez,et al.  The AR face database , 1998 .

[6]  Vladimir N. Vapnik,et al.  The Nature of Statistical Learning Theory , 2000, Statistics for Engineering and Information Science.

[7]  Hanqing Lu,et al.  Face detection using improved LBP under Bayesian framework , 2004, Third International Conference on Image and Graphics (ICIG'04).

[8]  Hyeonjoon Moon,et al.  The FERET Evaluation Methodology for Face-Recognition Algorithms , 2000, IEEE Trans. Pattern Anal. Mach. Intell..

[9]  Yehoshua Y. Zeevi,et al.  The Generalized Gabor Scheme of Image Representation in Biological and Machine Vision , 1988, IEEE Trans. Pattern Anal. Mach. Intell..

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

[11]  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.

[12]  Alex Pentland,et al.  Bayesian face recognition , 2000, Pattern Recognit..

[13]  Matti Pietikäinen,et al.  Face Recognition with Local Binary Patterns , 2004, ECCV.

[14]  Vladimir Naumovich Vapni The Nature of Statistical Learning Theory , 1995 .

[15]  Alex Pentland,et al.  Face recognition using eigenfaces , 1991, Proceedings. 1991 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[16]  Stan Z. Li,et al.  Shape localization based on statistical method using extended local binary pattern , 2004, Third International Conference on Image and Graphics (ICIG'04).

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

[18]  Tomaso A. Poggio,et al.  Face recognition: component-based versus global approaches , 2003, Comput. Vis. Image Underst..

[19]  Joachim M. Buhmann,et al.  Distortion Invariant Object Recognition in the Dynamic Link Architecture , 1993, IEEE Trans. Computers.

[20]  Wen Gao,et al.  Curse of mis-alignment in face recognition: problem and a novel mis-alignment learning solution , 2004, Sixth IEEE International Conference on Automatic Face and Gesture Recognition, 2004. Proceedings..

[21]  P. Jonathon Phillips,et al.  Face recognition vendor test 2002 , 2003, 2003 IEEE International SOI Conference. Proceedings (Cat. No.03CH37443).

[22]  Roberto Brunelli,et al.  Face Recognition: Features Versus Templates , 1993, IEEE Trans. Pattern Anal. Mach. Intell..