The thickness of the intima-media complex (IMC) of the common carotid artery (CCA) wall is important in the evaluation of the risk for the development of atherosclerosis. This paper presents a fully automated algorithm for the segmentation of the IMC. The segmentation of the IMC of the CCA wall is important for the evaluation of the intima media thickness (IMT) on B-mode ultrasound images. The presented algorithm is based on active contours and active contours without edges. It begins with image normalization, followed by speckle removal. The level set formulation of Chan and Vese using random initialization provides a segmentation of the CCA ultrasound (US) images into different distinct regions, one of which corresponds to the carotid wall region above the lumen whilst another corresponds to the carotid wall region below the lumen and includes the IMC. The results of the corresponding segmentation combined with anatomical information provide a very accurate outline of the lumen-intima boundary. This outline serves as an excellent initialization for segmentation of the IMC using parametric active contours. The method lends itself to the development of a fully automated method for the delineation of the IMC. The mean and standard deviation of the thickness of the automatically segmented regions are 0.65 mm +/-0.17 mm and the corresponding values for the ground truth IMT are 0.66 mm +/-0.18 mm. The Wilcoxon rank sum test shows no significant difference.