3D Face Recognition based on Radon Transform, PCA, LDA using KNN and SVM

Biometrics (or biometric authentication) refers to the identification of humans by their characteristics or traits. Bio-metrics is used in computer science as a form of identification and access control. It is also used to identify individuals in groups that are under surveillance. Biometric identifiers are the distinctive, measurable characteristics used to label and describe individuals. Three dimensional (3D) human face recognition is emerging as a significant biometric technology. Research interest into 3D face recognition has increased during recent years due to the availability of improved 3D acquisition devices and processing algorithms. Three dimensional face recognition also helps to resolve some of the issues associated with two dimensional (2D) face recognition. In the previous research works, there are several methods for face recognition using range images that are limited to the data acquisition and pre-processing stage only. In the present paper, we have proposed a 3D face recognition algorithm which is based on Radon transform, Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA). The Radon transform (RT) is a fundamental tool to normalize 3D range data. The PCA is used to reduce the dimensionality of feature space, and the LDA is used to optimize the features, which are finally used to recognize the faces. The experimentation has been done using three publicly available databases, namely, Bhosphorus, Texas and CASIA 3D face databases. The experimental results are shown that the proposed algorithm is efficient in terms of accuracy and detection time, in comparison with other methods based on PCA only and RT+PCA. It is observed that 40 Eigen faces of PCA and 5 LDA components lead to an average recognition rate of 99.20% using SVM classifier.

[1]  A. Averbuch,et al.  3D Fourier based discrete Radon transform , 2003 .

[2]  Patrick J. Flynn,et al.  A survey of approaches and challenges in 3D and multi-modal 3D + 2D face recognition , 2006, Comput. Vis. Image Underst..

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

[4]  Arman Savran,et al.  3D Face Recognition Benchmarks on the Bosphorus Database with Focus on Facial Expressions , 2008, BIOID.

[5]  H Moon,et al.  Computational and Performance Aspects of PCA-Based Face-Recognition Algorithms , 2001, Perception.

[6]  Yanfeng Sun,et al.  3D face recognition based on sparse representation , 2010, The Journal of Supercomputing.

[7]  Alan C. Bovik,et al.  Automated facial feature detection and face recognition using Gabor features on range and portrait images , 2008, 2008 15th IEEE International Conference on Image Processing.

[8]  Anil K. Jain,et al.  Matching 2.5D Scans for Face Recognition , 2004, ICBA.

[9]  Tieniu Tan,et al.  Automatic 3D face recognition combining global geometric features with local shape variation information , 2004, Sixth IEEE International Conference on Automatic Face and Gesture Recognition, 2004. Proceedings..

[10]  P. S. Hiremath,et al.  D Face Recognition Using Radon Transform and Symbolic PCA , 2012 .

[11]  V. Vijayakumari,et al.  Face Recognition Techniques: A Survey , 2013, International Journal of Advanced Trends in Computer Science and Engineering.

[12]  Rama Chellappa,et al.  Discriminant analysis of principal components for face recognition , 1998, Proceedings Third IEEE International Conference on Automatic Face and Gesture Recognition.

[13]  Andrea F. Abate,et al.  2D and 3D face recognition: A survey , 2007, Pattern Recognit. Lett..

[14]  Azriel Rosenfeld,et al.  Face recognition: A literature survey , 2003, CSUR.

[15]  Alan C. Bovik,et al.  Anthropometric 3D Face Recognition , 2010, International Journal of Computer Vision.

[16]  Patrick J. Flynn,et al.  Adaptive Rigid Multi-region Selection for Handling Expression Variation in 3D Face Recognition , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Workshops.

[17]  Alan C. Bovik,et al.  Texas 3D Face Recognition Database , 2010, 2010 IEEE Southwest Symposium on Image Analysis & Interpretation (SSIAI).

[18]  Rama Chellappa,et al.  Discriminant Analysis for Recognition of Human Face Images (Invited Paper) , 1997, AVBPA.

[19]  Rama Chellappa,et al.  Human and machine recognition of faces: a survey , 1995, Proc. IEEE.