Facial expression recognition using wavelet transform and local binary pattern
Akram Alsubari, D. N. Satange, Rakesh Jagdish Ramteke · 2017
This paper aims to experimental evaluation of different methodologies to recognize human face based on different facial expression. The face and facial images were captured locally, as the experiment is aimed to be done in India domain. The features were extracted based on two techniques, viz, Discrete Wavelet Transform (DWT) and Local Binary Pattern (LBP). The range of extracted feature is 150,300,600,1200 and 2400. Further, mean and standard deviation are computed for feature vector generation. Support Vector Machine (SVM) is used for classification/recognition. The experiment was carried out on different range of features as 160×15 samples. The result varies from 72% to 100% for various ranges of features. The performance of the proposed system is found to be satisfactory as compared to the existing system.