关键词: 表情识别, Curvelet变换, 小波变换, 特征提取

Abstract: For the wavelet transform has limitations to extract features of the edge of the images, a method of the facial expression recognition is proposed that using curvelet transform to extract features of the edge of the images. The curvelet transform can get more representation of sparse images than the wavelet transform on the representation of the singular of the edges of the image curve. The curvelet coefficient that can be got by using the curvelet transform on the facial images as the edge of the texture features can better reflect the changes in the facial expression, and the k-nearest neighbor algorithm is used to recognition different expression in this paper. The result shows that the method proposed in this paper is more effective than the wavelet transform in the expression recognition.

Key words: expression recognition, Curvelet transform, wavelet transform, feature extraction