Edge texture feature extraction and expression recognition based on curvelet

For the wavelet transform has limitations in extract features of the edge of images, a method of the facial expression recognition is proposed that using curvelet transform to extract features of the edge of 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 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 change in facial expression. As the same time, the k-nearest neighbor algorithm is used to recognize different expression in this paper. The result shows that the proposed algorithm in this paper is more effective than the wavelet transform in expression recognition. © 2013 IEEE.