We propose a fully automated algorithm for the segmentation of common carotid artery in longitudinal mode ultrasound images using active oblongs. The problem of segmentation and subsequent delineation of lumen-intima layer is solved as an optimization of a locally defined contrast function with respect to five degrees-of-freedom that characterize the active oblong. The detection of the common carotid artery and subsequent initialization of the active oblong inside the common carotid artery region has been done using a combination of binary thresholding, Hough transform, and pixel-offset operations. The algorithm has been validated on the Brno university signal processing lab B-mode ultrasound image database, which contains 84 longitudinal mode ultrasound images of the common carotid artery. The segmentation results are validated against the ground truth provided by two practising radiologists using Jaccard and Dice similarity measures. We have achieved a detection and segmentation accuracy of 95.2% and 97.5%, respectively.