New Parallel Models for Face Recognition

Subspace methods such as principal component analysis (PCA) and linear discriminant analysis (LDA) extract the features based on space domain. Transformation such as discrete cosine transform (DCT) extracts features based on frequency domain. In this paper, we present two parallel models which intend to utilize the features extracted from frequency and space domain of facial images. Both features are combined under a fusion based scheme. FERET database is chosen to evaluate the performance of the proposed method. Simulation results indicate that the proposed method outperforms other traditional methods and enhance the representation of facial image under low-dimensional features.

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

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

[3]  Svetha Venkatesh,et al.  Face Recognition via the Overlapping Energy Histogram , 2007, IJCAI.

[4]  Ja-Chen Lin,et al.  A new LDA-based face recognition system which can solve the small sample size problem , 1998, Pattern Recognit..

[5]  Ling Guan,et al.  Image retrieval based on energy histograms of the low frequency DCT coefficients , 1999, 1999 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings. ICASSP99 (Cat. No.99CH36258).

[6]  Yuehui Chen,et al.  Face Recognition Using DCT and Hierarchical RBF Model , 2006, IDEAL.

[7]  Meng Joo Er,et al.  PCA and LDA in DCT domain , 2005, Pattern Recognit. Lett..

[8]  Ajith Abraham,et al.  Texture classification based on DCT and soft computing , 2001, 10th IEEE International Conference on Fuzzy Systems. (Cat. No.01CH37297).

[9]  Hua Yu,et al.  A direct LDA algorithm for high-dimensional data - with application to face recognition , 2001, Pattern Recognit..

[10]  René David,et al.  Asymptotic continuous Petri nets , 1993, Discret. Event Dyn. Syst..

[11]  Abbes Amira,et al.  Multiresolution Hybrid Approaches for Automated Face Recognition , 2007, Second NASA/ESA Conference on Adaptive Hardware and Systems (AHS 2007).

[12]  Lawrence Sirovich,et al.  Application of the Karhunen-Loeve Procedure for the Characterization of Human Faces , 1990, IEEE Trans. Pattern Anal. Mach. Intell..

[13]  Konstantinos N. Plataniotis,et al.  Face recognition using LDA-based algorithms , 2003, IEEE Trans. Neural Networks.

[14]  W.J. Phillips,et al.  Comparative performance of principal component analysis, gabor wavelets and discrete wavelet transforms for face recognition , 2005, Canadian Journal of Electrical and Computer Engineering.

[15]  D. Lefebvre,et al.  Fuzzy control of variable speed continuous Petri nets , 1999, Proceedings of the 38th IEEE Conference on Decision and Control (Cat. No.99CH36304).

[16]  Jing-Yu Yang,et al.  A generalized optimal set of discriminant vectors , 1992, Pattern Recognit..

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