Range data from stereo images of edge points

The author presents an algorithm and implementation for recovering range data from stereo images of edge points. The recovered data are used for object identification and localization. Parallel laser light planes are projected on a polyhedral object. The light planes appear as a set of broken straight segments in images. Discontinuities along these straight segments correspond to normal discontinuities on the underlying surfaces. Points of discontinuities in the image are extracted as edge points and they lie on edges of the underlying object. Matching edge points between stereo images give range data. The matching algorithm uses the epipolar constraint, a relational constraint, and an ordering constraint. The range data can be arranged in order according to the light planes to which they belong. Experimental results of the matching process and the accuracy of recovered data are presented.<>