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For autonomously acting robots and driver assistance systems powerful optical stereo sensor systems are required. Object positions and environmental conditions have to be acquired in real-time. In this paper an algorithm based on a hardware-software co-design is applied. A depth-map is generated with a hierarchical detection method. A depth-histogram is generated by using the density distribution of the disparity in the depth-map. It is used for object detection. The object clustering can be accomplished without calculation of 3D-points, due to the almost identical mapping of the objects over the whole distance, within the histogram. A lane detection is applied by using a Hough transform. The suitability at night and the detection of small objects like bikers is proven.