An Effective Application of Illumination Invariant Transform on Face Recognition
This paper presents an image quality based face recognition system. Face recognition which plays a vital role in surveillance and security applications. The significance of this system is that it recognizes faces at different illumination conditions, facial expressions, pose and occlusion, among which the recognition at varying illumination conditions have greater accuracy. A practically easible and a challenging technique are employed in this project work. Image quality based approach has been used for recognizing face and identifying a person to increase recognition accuracy and to avoid misidentification. Histogram equalization is used as preprocessing method. The importance of histogram equalization is to normalize the illumination variations. The DWT is used for dimensionality reduction by reducing the number of samples thereby increasing the speed. This system provided 98.6% accuracy in recognizing faces from a set of 2680 images; we evaluate our approach on PIE, AT and T, MIT, Georgia tech face, PICS AR, Bao and GTAVE face database.