A new ground segmentation method for obstacle detection using possibility theory

This paper presents a new method of ground segmentation for obstacle detection using possibility theory. Data provided by reference area is extracted and modeled separately using possibility theory. The obtained possibility maps are combined with an operator which can manage the uncertainty and ambiguity in the images. The final segmented image is constructed in decision step.