Facial Expression Recognition Based on Specific Regions Wavelet Decomposition, Local Directional Number Pattern and Sparse Representation

A new method for facial expression recognition is presented in this paper. Our method offers basically three benefits: first, it is combining regional compression with wavelet decomposition to preprocess the facial image, which can effectively remove interference and enhance useful information. Second, local directional number pattern (LDN) is adopted to extract the facial feature, it is not only encode the intensity transitions of the image but also encode the directional information, which is more effective to represent the feature. The last, sparse representation classification method is used to represent the test expression image by the linear combination of the training expression images. Results show that our method is effective.