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Facial recognition is one of the most popular issues in the field of pattern recognition. Face recognition with uncontrolled lighting conditions is more significant than the physical characteristics of individual faces. Uncontrolled lighting from the right and left can affect the face image. A lot of research on facial recognition, but little attention given to the face image is symmetrical object. Several studies to explore and exploit the symmetrical properties of the face for face recognition were performed. In this paper, we propose a pre-processing method to solve one of the common problems in facial images with varying illumination. We utilize the symmetric property of the face then performed gamma correction then classified using Robust Regression. The results of this experiment got an average accuracy of 94.31% and the proposed technique improves recognition accuracy especially in images with extreme lighting conditions using gamma correction parameters γ = 0.3.

Preprocessing With Symmetrical Face And Gamma Correction For Face Recognition Under Varying Illumination With Robust Regression Classification