Facial Expression Recognition by Calculating Euclidian Distance for Eigen Faces Using PCA

In this paper the proposed methodology is to recognize Facial expressions of human being by using Eigen Faces. For recognition of human expression, in this approach we consider the following steps: face detection, facial feature extraction and then facial expression classification. The proposed system is based on calculating the Euclidian distance for the Eigen Faces. In this approach we will consider all the seven basic emotions which are classified as happy, anger, sad, fear, and disgust, surprised, neutral. Here 50 facial expression images are considered and trained by Eigen Faces. Finally the featured Eigen Faces are compared with the test image. In our approach face recognition is done by “Principal component analysis (PCA)”. The experimental result gives 98.5% recognition rates for each emotion.