Real-time qualitative road traffic data analysis is the cornerstone for any modern transport system. So far, most of the analysis is done manually and the use of image processing techniques for qualitative analysis is at its early stage. In this paper we describe novel image processing algorithms together with the results, which assign a qualitative description to a traffic scene. The qualitative description of a traffic scene can be used for controlling traffic lights and putting hazard signals on the road side, thereby warning drivers to slow down or direct them to alternative routes. We analyse a wider view of the path and evaluate the whole description of traffic status. To approach this, we considered two major parameters of traffic status: the percentage of road occupied by vehicles and the percentage of moving and stationary parts of this occupancy. The alogrithm developed for traffic analysis automatically divides the scene into a number of blocks, based on camera parameters and the number of lanes. This full frame image processing application requires a low-cost frame grabber and a Pentium-based computer system for on-line real-time operations.