International Journal of Artificial Intelligence and Neural Networks
Author(s) : AKASH DHORAJIYA, MAHESH GOYANI, RONAK PAUN
Since last decade, face recognition has replaced almost all biometric authentication techniques available. Many algorithms are in existence today based on various features. In this paper, we have compared the performance of various classifiers like correlation, Artificial Neural Network (ANN) and Support Vector Machine (SVM) for Face Recognition. We have proposed face recognition based on discriminative features. Holistic features based methods Fisher Discriminant Analysis (FDA) usused to extract out discriminative features from the input face image respectively. These features are used to train classifiers like Artificial Neural Network (ANN) and Support Vector Machine (SVM). Results in the last section describe the accuracy of proposed scheme.