In this paper, an automatic facial expression recognition system is presented. When a face image is input, two inner canthi are detected as the reference points for searching the expression features extracted from the contour and displacement of eyebrows, eyes, and mouth. Our feature extraction method can reduce the partial influence of shadows and noises. Finally, the expression features are used as the input to an Elman Neural Network of classifiers. The results on the JAFFE facial database show an average recognition accuracy of 84.7% in seven expressions by automatic canthi detection and 92.2% by manual canthi detection.