The atherosclerotic plaque in the intravascular ultrasound image is mainly thickened by the intima and endominal tissue, which leads to the narrowing of the transverse section of the lumen and the identification of the types of atherosclerotic plaques, which can provide guidance for clinical treatment. Atherosclerotic plaques were mainly composed of lipid plaques, fibrous plaques and calcified plaques, and their echo intensity increased in turn. The texture feature information of arterial plaque image is extracted from the distribution of image pixel gray level in space, and three kinds of feature extraction methods are selected, such as GLCM, LBP, NGL. The extracted features are classified by the support vector machine (SVM) and the error correcting output codes (ECOC). The results show that the classification accuracy of the three feature extraction methods is better.