New area- and edge-based stereo algorithm and its experimental demonstration using natural objects
Gennady M. Reitblat, Arne Skov Jensen · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1997
We present a new stereo algorithm which includes some features of area-based and edge-based approaches, eliminating their main drawbacks. An addition to usual pre- and post-processing steps, the algorithm includes a new solution of correspondence problem For each left edge point within the some support area we search at first the possible corresponding points in the right image selecting than only the single candidate having the maximum support sum. To find a support sum for each disparity candidate, we use a disparity gistogram taking the magnitude of the nearest gistogram peak as a support sum. To find a support sum for each disparity candidate, we use a disparity gistogram taking the magnitude of the nearest gistogram peak as a support sum to be found. To reject false matches, each support area is classified depending on fraction F of edge points connected with the major gistogram peak. If F is more than some threshold, say 80 percent, all points not connected with the major peak are simply rejected marking the rest points as a true. In opposite case, more complicated procedure is used taking into account the edge contours information by testing it for some global consistency constrains. The algorithm have been successfully tested using specially developed computer program operating with different natural objects including some hard features.