Efficient Identification System Using Wavelet Transform and Average Half-Face

Face recognition based on biometrics is one of the most hot and challengeable technologies. This paper proposes an efficient technique for identification of an individual. The person identification is done by face recognition using an average half face as a feature. Discrete Wavelet Transform (DWT) is used for feature extraction and Support Vector Machine (SVM) is proposed for classification. The proposed system consists of three phases: (i) Preprocessing, (ii) Feature extraction and (iii) Classification. The proposed method was tested using the cropped extended Yale database, where the images vary in illumination and expression. The experiment was demonstrated with various thresholds. Better results were obtained for a threshold of 0.5. The proposed system shows a high degree of success in identifying the individual with reduced computation time and memory storage saving of 31%.