Robust Face Recognition Technique under Varying Illumination

Journal of Applied Research and Technology - Tập 13 - Trang 97-105 - 2015
Jamal Hussain Shah1, Muhammad Sharif1, Mudassar Raza1, Marryam Murtaza1, Saeed-Ur-Rehman1
1Department of Computer Science COMSATS Institute of Information Technology Wah Cantt., 47040, Pakistan

Tài liệu tham khảo

Chellappa, 1995, Human and machine recognition of faces: A survey, Proceedings of the IEEE, 83, 705, 10.1109/5.381842 Zhao, 2003, Face recognition: A literature survey, Acm Computing Surveys (CSUR), 35, 399, 10.1145/954339.954342 Sharif, 2012, Enhanced and Fast Face Recognition by Hashing Algorithm, Journal of Applied Research and Technology (JART), 10, 607 RamÃrezâ, 2009, 3D-facial expression synthesis and its application to face recognition systems, JART, 7, 354 Zhang, 2008, Topology preserving non-negative matrix factorization for face recognition, Image Processing, IEEE Transactions on, 17, 574, 10.1109/TIP.2008.918957 Shim, 2008, A subspace model-based approach to face relighting under unknown lighting and poses, Image Processing, IEEE Transactions on, 17, 1331, 10.1109/TIP.2008.925390 Liu, 2008, A hybrid color and frequency features method for face recognition, Image Processing, IEEE Transactions on, 17, 1975, 10.1109/TIP.2008.2002837 Pizer, 1987, Adaptive histogram equalization and its variations, Computer vision, graphics, and image processing, 39, 355, 10.1016/S0734-189X(87)80186-X Shan, 2003, Illumination normalization for robust face recognition against varying lighting conditions, 157 Savvides, 2003, 549 Jacobs, 1998, Comparing images under variable illumination”. In: Computer Vision and Pattern Recognition, 610 Tumblin, 1999, LCIS: A boundary hierarchy for detail-preserving contrast reduction, 83 Pentland, 1994, View-based and modular eigenspaces for face recognition, 84 Georghiades, 2000, From few to many: Generative models for recognition under variable pose and illumination, 277 Georghiades, 2001, From few to many: Illumination cone models for face recognition under variable lighting and pose, Pattern Analysis and Machine Intelligence, IEEE Transactions on, 23, 643, 10.1109/34.927464 Basri, 2003, Lambertian reflectance and linear subspaces, Pattern Analysis and Machine Intelligence, IEEE Transactions on, 25, 218, 10.1109/TPAMI.2003.1177153 Basri, R. and D.W. Jacobs, “Lambertian reflectance and linear subspaces”, Google Patents, Vol. no. pp.2005. Batur, 2001, Linear subspaces for illumination robust face recognition Horn, 1986 Stockham, 1972, Image processing in the context of a visual model, Proc. IEEE, 60, 828, 10.1109/PROC.1972.8782 Land, 1971, Lightness and retinex theory, JOSA, 61, 1, 10.1364/JOSA.61.000001 Jobson, 1997, A multiscale retinex for bridging the gap between color images and the human observation of scenes, Image Processing, IEEE Transactions on, 6, 965, 10.1109/83.597272 Shashua, 2001, The quotient image: Class-based re-rendering and recognition with varying illuminations, Pattern Analysis and Machine Intelligence, IEEE Transactions on, 23, 129, 10.1109/34.908964 Wang, 2004, Generalized quotient image Wang, 2004, Face recognition under varying lighting conditions using self quotient image, 819 Gross, 2003, An image preprocessing algorithm for illumination invariant face recognition, 10 Chen, 2006, Total variation models for variable lighting face recognition, Pattern Analysis and Machine Intelligence, IEEE Transactions on, 28, 1519, 10.1109/TPAMI.2006.195 Chen, 2000, In search of illumination invariants, 254 Samal, 1992, Automatic recognition and analysis of human faces and facial expressions: A survey, Pattern recognition, 25, 65, 10.1016/0031-3203(92)90007-6 Govindaraju, 1989, Locating human faces in newspaper photographs, 549 Edelman, 1994, A system for face recognition that learns from examples, 787 Daugman, 1985, Uncertainty relation for resolution in space, spatial frequency, and orientation optimized by two-dimensional visual cortical filters, JOSA A, 2, 1160, 10.1364/JOSAA.2.001160 Liu, 2009, Learning kernel in kernel-based LDA for face recognition under illumination variations, Signal Processing Letters, IEEE, 16, 1019, 10.1109/LSP.2009.2027636