Facial Expression Recognition Using PCA-RBFNN Method and Local Feature Extraction

Facial Expression Recognition is still standing out amongst the most difficult issues in biometric systems. In this study, we implement Facial Expression Recognition using Principal component analysis (PCA) and Radial Basis Function Neural network (RBFNN) approach. We extract facial expression features using local method. The proposed system works in three parts. First Pre-processing: where median filtering is done to make faces prepared for feature extraction, then Feature extraction: where local features (Entropy, Mean, Standard Deviation and Euler coefficient) based projection elements are extracted which are utilized to recognize the distinctive faces. In the experimental results, we improved facial expression recognition accuracy in terms of recognition rate is 99.53% with database of JAFFEE (84 faces of 12 persons).