Local Illumination Normalization and Facial Feature Point Selection for Robust Face Recognition
Keywords:Face recognition, Illumination normalization, Robustness, Gabor wavelet, Feature point, ICA, HMM, AAM
Face recognition systems must be robust to the variation of various factors such as facial expression, illumination, head pose and aging. Especially, the robustness against illumination variation is one of the most important problems to be solved for the practical use of face recognition systems. Gabor wavelet is widely used in face detection and recognition because it gives the possibility to simulate the function of human visual system. In this paper, we propose a method for extracting Gabor wavelet features which is stable under the variation of local illumination and show experiment results demonstrating its effectiveness.
Aguerrebere, C., Capdehourat, G., Delbracio, M., Mateu, M., Fernandez, A.; Lecumberry, F. : An Improved Face Recog- nition Algorithm through Gabor Filter Adaptation, Automatic Identification Advanced Technologies, 2007 IEEE Workshop on 7-8 June, 2007, 74-79
Ahonen, T.; Hadid, A.; Ainen M. P. ; Face Recognition with Local Binary Patterns, ECCV 2004, LNCS 3021, 2004, 469–481.
Bow, S.T.; Pattern Recognition and Image Preprocessing (Ed. K. J. Ray Liu, Signal Processing and Communications), Marcel Dekker, Inc, 2002.
Chen, W.; M. Joo Er and S. Wu; Illumination Compensation and Normaliza- tion for Robust Face Recognition Using Discrete Cosine Transform in Logarithm Domain, IEEE Transactions On Systems, Man, and Cybernetics - Part B: Cybernetics, Vol. 36, No. 2, April 2006, 458-466.
Delac,K.; Grgic, M.; Grgic, S.; Generalization Abilities of Appearance- Based Subspace Face Recognition Algorithms, Technical Report, FER-VCL-TR- 2005-01, University of Zagreb, FER, 2005,
Delac, K.; Grgic, M. ; Grgic, S.; Statistics in Face Recognition : Analyzing Probability Distributions of PCA, ICA and LDA Performance Results, Technical Report, FER-VCL-TR-2005-03, University of Zagreb, FER, 2005, Image and Signal Processing and Analysis, 2005. Proceedings of the 4th International Symposium on 15-17 Sep. 2005, 289 - 294
Edwards, G. J. ; Cootes, T. F. ; Taylor, C. J.; Active appearance models, IEEE Trans.on PAMI, Vol.23, no.6, 2001, 681-685.
Edwards, G.; Cootes, T. F. ; Taylor, C. J. ; Face recognition using active appearance models, in Proc. European Conference on Computer Vision, Vol.2, 1998, 581-695.
Fukunaga, K., Introduction to Statistical Pattern Recognition, Academic Press, 1990.
Kotropoulos, C.; Tefas, A. ; I. Pitas; Mor- phological Elastic Graph Matching applied to frontal face authentication under well-controlled and real conditions, Pattern Recognition, Vol.13, no.12, 2000, 1935-1947.
Lu, X.; Image Analysis for Face Recognition, Department of Computer Science & Engineering, Michigan State university, East Lansing, MI, 48824, http://www.scribd.com/doc/39310482/Image-Analysis-for-Face-Recognition
Marcel, S.; Rodriguez, Y., Heusch G.; On the Recent Use of Local Binary Patterns for Face Authentication, IDIAP-RR 06-34, to appear in International Journal on Image and Video Processing Special Issue on Facial Image Processing, 2007
Martinez, A. M. ; Kak, A. C.; PCA versus LDA, IEEE Trans.on PAMI, Vol.23, no.2, 2001, 228-233.
Maturana, D. ; Mery, D. ; Soto, A. ; Face Recognition with Local Binary Patterns, Spatial Pyramid Histograms and Naive Bayes Nearest Neighbor classification, 2009 International Conference of the Chilean Computer Science Society, 2009, 125-132.
Ojala, T.; Pietikäinen, M. ; Mäenpää, T., Multiresolution Gray-scale and Rotation Invariant Texture Classification with Local Binary Patterns, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.24, no.7, 2002, 971-987.
Pang, Y. ; Zhang, L. ; Li, M. ; Liu Z. ; W. Ma; A Novel Gabor-LDA Based Face Recognition Method, PCM 1, Vol. 3331, Springer, 2004, 352-358.
Phillips, P., Moon, H., Rizvi, S., Rauss, P., The FERET Evaluation Methodology for Face-Recognition Algorithms, IEEE Trans. on PAMI, Vol.22, no.10, 2000, 1090-1104.
Shakhnarovich, G. ; Moghaddam, B.; Face Recognition in Subspace, Springer- Verlag, 2004.
Sharif, M., Khalid, A., Raza, M., S. MOHSIN; Face Recognition using Gabor Filters, Journal of Applied Computer Science & Mathematics, no. 11 (5) /2011, Suceava, 53-57
Su, Y.; Shan, S.; X. Chen; W. Gao; Hierarchical Ensemble of Global and Local Classifiers for Face Recognition, IEEE Transactions on Image Processing, vol 18 Issue 8, 2009, 1885-1896.
Theodoridis, S.; Koutroumbas, K. ; Pattern Recognition, Fourth Edition, Academic press, 2009
Turk, M.; Pentland A. ; Eigenfaces for Recognition, Journal of Cognitive Neuroscience, Vol.3, no.1, 1991, 72-86.
Webb, Andrew R. ; Statistical Pattern Recognition, Wiley-Blackwell (an imprint of John Wiley & Sons Ltd), 2011
Wiskott, L.; Fellous, J.; Malsburg, C. V.; Face Recognition by Elastic Bunch Graph Matching, IEEE Trans.on PAMI, Vol.19, no.7, pp.775-779, 1997.
Zhao, W.; Chellappa, R.; Phillips, P. J.; Rosenfeld, A.; Face Recognition: A Literature Survey, ACM Computing Surveys, Vol. 35, No. 4, December 2003, 399–458.
How to Cite
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).
- The author(s) is responsible for the correctness and legality of the paper content.
- Papers that are copyrighted or published will not be taken into consideration for publication in JMEDS It is the author(s) responsibility to ensure that the paper does not cause any copyright infringements and other problems.
- It is the responsibility of the author(s) to obtain all necessary copyright release permissions for the use of any copyrighted materials in the paper prior to the submission.
- The Author(s) retains the right to reuse any portion of the paper, in future works, including books, lectures and presentations in all media, with the condition that the publication by JMEDS is properly credited and referenced.
JMEDS articles by Journal of Mobile, Embedded and Distributed Systems (JMEDS) is licensed under a Creative Commons Attribution 4.0 International License.
Based on a work at http://jmeds.eu.
Permissions beyond the scope of this license may be available at http://jmeds.eu/index.php/jmeds/about/submissions#copyrightNotice.