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An extension to the rank constraint for improving the reliability of stereo matching algorithms using the rank transform

By Jasmine Banks, Mohammed Bennamoun, Kurt Kubik and Peter Corke


The rank transform is one non-parametric transform which has been applied to the stereo matching problem The advantages of this transform include its invariance to radio metric distortion and its amenability to hardware implementation. This paper describes the derivation of the rank constraint for matching using the rank transform Previous work has shown that this constraint was capable of resolving ambiguous matches thereby improving match reliability A new matching algorithm incorporating this constraint was also proposed. This paper extends on this previous work by proposing a matching algorithm which uses a dimensional match surface in which the match score is computed for every possible template and match window combination. The principal advantage of this algorithm is that the use of the match surface enforces the left�right consistency and uniqueness constraints thus improving the algorithms ability to remove invalid matches Experimental results for a number of test stereo pairs show that the new algorithm is capable of identifying and removing a large number of in incorrect matches particularly in the case of occlusion

Topics: 080104 Computer Vision, 080106 Image Processing, image matching, rank transform, stereo vision
Publisher: IEEE
Year: 1999
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