Accurate data collection and interpretation of pavement data is critical for the decision-making process in pavement management. Collection of several data types for pavement management is automated and widely used. However, collection and analysis of pavement surface distress is still a manual process for many highway agencies, even though substantial amount of resources were used in the past decades to devise automated approaches for collecting and analyzing pavement surface distress. This paper introduces a new automated system capable of collecting and analyzing pavement surface distress, primarily cracks, in real-time through the use of high resolution digital camera, efficient image processing algorithms and multi-computer, and multi-CPU based parallel computing. The paper overviews the major steps in the algorithms for image processing. It is shown in the paper that distress results from the automated system are consistent for multiple passes of the same pavement sections.