Facial expression feature extraction method based on improved LBP
WANG Si-ming, LIANG Yun-hua · DOAJ (DOAJ: Directory of Open Access Journals) · 2019
Local binary pattern（LBP） is an important method for texture feature extraction of facial expression. However, it also has the shortcomings of high dimension, slow feature extraction and noeffective local or global features extracted. To solve these problems, a facial expression feature extraction method is proposed based on improved LBP. Firstly, LBP is converted into double local binary pattern（DLBP）. Then by combining Taylor expansion（TE） with DLBP, DLBP-TE algorithm is obtained. Finally, the DLBP-TE algorithm combined with extreme learning machine（ELM） is applied in seven kinds of ficial expression images and the corresponding experiments are carried out in Japanese adult female facial expression（JAFFE） database. The results show that the proposed method can significantly improve facial expression recognition rate.