AUTOMATIC VEHICLE DETECTION IN SPACE IMAGES SUPPORTED BY DIGITAL MAP DATA

Due to increasing traffic there is high demand in traffic monitoring of densely populated urban areas. In our approach we focus on the detection of vehicle queues and use a priori information of roads location and direction. In high resolution satellite imagery single vehicles can hardly be separated since they are merged to either dark or bright ribbons. Initial hypotheses for the queues can be extracted as lines in scale space which represent the centres of the queues. We exploit the fact that vehicle queues are composed of repetitive patterns. For discrimination of single vehicles a width function of the queues is calculated in the gradient image and the variations of the width function are analyzed. We show intermediate and final results of processing a panchromatic QuickBird image covering a part of an inner city area.