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Machine Vision Applied to Vehicle Guidance

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4 Author(s)
R. M. Inigo ; School of Engineering and Applied Science, University of Virginia, Charlottesville, VA 22901. ; E. S. Mcvey ; B. J. Berger ; M. J. Wirtz

Research on the semiautonomous operation of mobile robots in typical pathways is described. The image of the pathway will consist of two nearly vertical lines bounding a region with little texture (the pathway) after correction for perspective. In order to identify pathway boundaries, regions in the image space are examined using an edge detection algorithm, edges between regions are determined by the algorithm, and those corresponding to straight or nearly straight lines with large slope (path boundaries) are identified by means of the Hough transform. Once the path boundaries are identified, the horizontal distance from camera to road edge is determined. Next, a method to detect cubics in the roadway (i.e., obstacles) is presented. The region of interest in the roadway (from the camera to some predetermined distance in front of it) is known from the path boundary algorithm. The interior of this region is examined for edges. If edges are detected, it means that obstacles or shadows are present. A method to separate obstacles from shadows using stere vision is then presented.

Published in:

IEEE Transactions on Pattern Analysis and Machine Intelligence  (Volume:PAMI-6 ,  Issue: 6 )