A New Method for Face Recognition Using Wavelet

Content-Based Image Retrieval (CBIR) allows to automatically extracting target images according to objective visual contents of the image itself. Representation of visual features and similarity match are important issues in CBIR. In this paper an attempt is made to review a wide range of methods used for face recognition comprehensively. This include PCA, LDA, ICA, SVM, Gabor wavelet tool for recognition .This review investigates all these methods with parameters that challenges face recognition like illumination, pose variation, facial expressions.

[1]  Stephen P. Banks,et al.  Signal Processing, Image Processing and Pattern Recognition , 1991 .

[2]  Alice J. O'Toole,et al.  Face recognition algorithms and the other-race effect: computational mechanisms for a developmental contact hypothesis , 2002, Cogn. Sci..

[3]  Aleix M. Martínez,et al.  Recognizing Imprecisely Localized, Partially Occluded, and Expression Variant Faces from a Single Sample per Class , 2002, IEEE Trans. Pattern Anal. Mach. Intell..

[4]  Adnan Acan,et al.  Multiple classifier implementation of a divide-and-conquer approach using appearance-based statistical methods for face recognition , 2004, Pattern Recognit. Lett..

[5]  Pengfei Shi,et al.  Image PCA: A New Approach for Face Recognition , 2007, 2007 IEEE International Conference on Acoustics, Speech and Signal Processing - ICASSP '07.

[6]  V. P. Vishwakarma,et al.  A Novel Approach for Face Recognition Using DCT Coefficients Re-scaling for Illumination Normalization , 2007, 15th International Conference on Advanced Computing and Communications (ADCOM 2007).

[7]  E. Walia.  Face Recognition Using Improved Fast PCA Algorithm , 2008, 2008 Congress on Image and Signal Processing.

[8]  Haiping Lu,et al.  MPCA: Multilinear Principal Component Analysis of Tensor Objects , 2008, IEEE Transactions on Neural Networks.

[9]  Mandeep Kaur,et al.  Recognition of Facial Expressions with Principal Component Analysis and Singular Value Decomposition , 2010 .

[10]  Jeet Kumar,et al.  An Efficient Pose Invariant Face Recognition System , 2011, SocProS.

[11]  M. Mani Roja,et al.  Face recognition using discrete cosine transform for global and local features , 2011, 2011 INTERNATIONAL CONFERENCE ON RECENT ADVANCEMENTS IN ELECTRICAL, ELECTRONICS AND CONTROL ENGINEERING.

[12]  Goel Tripti,et al.  Comparative Analysis of various Illumination Normalization Techniques for Face Recognition , 2011 .

[13]  David J. Kriegman,et al.  Two faces are better than one: Face recognition in group photographs , 2011, 2011 International Joint Conference on Biometrics (IJCB).

[14]  D. K. Das.  Comparative Analysis of PCA and 2DPCA in Face Recognition , 2012 .

[15]  Vinay Rishiwal,et al.  Improved PCA Algorithm for Face Recognition - TI Journals , 2012 .

[16]  D. K. Basu,et al.  Face Recognition Using Appearance Based Approach: A Literature Survey , 2012 .

[17]  A. R Kulkarni,et al.  An Improved Hybrid Face Recognition Based on PCA and Subpattern Technique , 2013 .

[18]  Bruce A. Draper,et al.  Computational Statistics and Data Analysis Introduction to Face Recognition and Evaluation of Algorithm Performance , 2022 .

[19]  Muhammad Waqas Anwar,et al.  A Multifaceted Independent Performance Analysis of Facial Subspace Recognition Algorithms , 2013, PloS one.

[20]  Eric C. C. Tsang,et al.  Face Recognition Using Genetic Algorithm , 2014, ICMLC.

[21]  Parul M. Jain,et al.  A Survey on Face Recognition in Present Scenario , 2014 .

[22]  Virendra P. Vishwakarma,et al.  Illumination normalization using fuzzy filter in DCT domain for face recognition , 2015, Int. J. Mach. Learn. Cybern..

[23]  Harjinder Singh,et al.  A Review Paper on Face Recognition Techniques , 2016 .