PREPROCESSING WITH SYMMETRICAL FACE AND GAMMA CORRECTION FOR FACE RECOGNITION UNDER VARYING ILLUMINATION WITH ROBUST REGRESSION CLASSIFICATION - Eva Y Puspaningrum; Budi Nugroho; Andri Istifariyanto (Jurnal Ilmiah Kursor, 2017)
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 thephysical characteristics of individual faces. Uncontrolled lighting from the right and leftcan affect the face image. A lot of research on facial recognition, but little attention givento the face image is symmetrical object. Several studies to explore and exploit thesymmetrical properties of the face for face recognition were performed. In this paper, wepropose a pre-processing method to solve one of the common problems in facial imageswith varying illumination. We utilize the symmetric property of the face then performedgamma correction then classified using Robust Regression. The results of this experimentgot an average accuracy of 94.31% and the proposed technique improves recognitionaccuracy especially in images with extreme lighting conditions using gamma correctionparameters γ = 0.3.