Symmetrical Face Images and Gamma Correction Technique for Face Recognition under Varying Illumination

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Eva Y Puspaningrum


Face recognition with various illumination is one of the most important challenges for practical face recognition systems. Under uncontrolled lighting condition is more significant than the physical characteristics of the individual face. The Impact of lighting uncontrolled lighting from the right and left side so that it can affect the face image. There are many studies on face recognition, but only little attention is paid to   face image is an axis-symmetrical objects. Few studies to explore and exploit the axis-symmetrical property of faces for face recognition are conducted. In this paper, we discuss the pre-processing method to solve one of the common problems in face images with lighting variations. We take the axis-symmetrical of faces then a gamma-correction process for pre-processing that will then be done by robust regression classification (RRC). Experimental results on Yale Face Database B 50x50 with illumination problems show that the proposed technique improves recognition accuracy especially in images with extreme lighting conditions using gamma correction parameter γ = 0.3


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PUSPANINGRUM, Eva Y. Symmetrical Face Images and Gamma Correction Technique for Face Recognition under Varying Illumination. Jurnal Ilmiah Kursor, [S.l.], v. 9, n. 2, apr. 2018. ISSN 2301-6914. Available at: <>. Date accessed: 22 apr. 2018.


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