Abstract
This paper presents new methods of the illumination normalization in images preprocessed for face recognition system. The main problem in statistical methods of face recognition is illumination. Different lighting conditions between photos taken indoor and outdoor may drastically decrease the level of correct classification. Variations of the illumination lie mostly in low-frequency band, so it is possible to use several transforms operating on frequency domain of an image. This approach is to truncate appropriate number of coefficients in frequency domain to minimize variations under different lighting conditions. This paper presents methods using transforms such as: Two Dimensional Discrete Cosine Transform type II (2D-DCT-II) and two Periodic Piecewise-Linear Transforms, such as: Periodic Haar piecewise Linear Transform (PHL) and Periodic Walsh piecewise-Linear Transform PWL. The main advantage of this approach is that, it does not require any modeling steps and it can be implemented in real-time face recognition systems.
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© 2012 ICST Institute for Computer Science, Social Informatics and Telecommunications Engineering
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Orzechowski, T.M., Dziech, A., Lukanko, T., Rusc, T. (2012). The Use of Selected Transforms to Improve the Accuracy of Face Recognition for Images with Uneven Illumination. In: Atzori, L., Delgado, J., Giusto, D. (eds) Mobile Multimedia Communications. MobiMedia 2011. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 79. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-30419-4_21
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DOI: https://doi.org/10.1007/978-3-642-30419-4_21
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