FACIAL EXPRESSION RECOGNITION BASED ON PRINCIPAL COMPONENTS ANALYSIS

Recognizing facial expression is one of the most effective applications of image processing and has obtained great attention in latest years. A recognition system for facial expression is a computer based application which detects an individual facial expression for the purposes of authentication, criminal identification, passport verification, estimating age, and various other purposes. In this study, we propose a human recognition system based on facial expression. The system depends on extracting features using Principal Component Analysis (PCA) which later used in the training and recognition steps. The system is able to recognize diverse facial expressions such as Neutral, Anger, Disgust ,Fear, Happy, Sad and Surprise. The primary objective of this study is to improve the efficiency and to achieve better recognition rate using Support Vector Machine (SVM). The system is evaluated using the registered JAFFE Dataset of face images. The results show that or proposed system is robust and maintain high recognition rate.