Face Recognition under Varying Illumination Condition

This project demostrates a GUI-based face recognition under complex illumination conditions using state-of-the-art methods and a new method

This projects attempts to demonstrate the accuracy and efficiency of several state-of-th-art method for face recognition under varying illumination conditions. Some of these methods ar GradientFaces, Weber Faces, DCT Normalization, DOG, MSR and SSR. An interractive GUI-based system has been developed for training the face images in question and testing their identification rate using the Principle Component Analysis (PCA) Method. Later, a new method was proposed that was later discovered to outperform other state-of-the-art methods (although under varying conditions).