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Fuzzy Sets Based Improvement of a Stereo Matching Algorithm with Balanced Correlation Window and Occlusion Detection

Abstract : This paper presents an ameliorated version of the Zitnick and Kanade stereo algorithm. The novelties in our algorithm are the use of a balanced correlation window, the use of a new factor in the calculation of initial matching values which expresses the possibility of matching between two pixels and a new iterative function for the refinement of the initial matching values. Experimental results are evaluated on synthetic and real images and a comparison of our results to those of many state-of-the-art methods, using the ground truth data supplied by the University of Tsukuba, is presented.
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https://hal-lirmm.ccsd.cnrs.fr/lirmm-00993594
Contributor : Haythem Ghazouani <>
Submitted on : Tuesday, May 20, 2014 - 3:16:22 PM
Last modification on : Friday, June 7, 2019 - 11:06:02 AM
Long-term archiving on: : Wednesday, August 20, 2014 - 11:41:42 AM

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Haythem Ghazouani, René Zapata, Tagina Moncef. Fuzzy Sets Based Improvement of a Stereo Matching Algorithm with Balanced Correlation Window and Occlusion Detection. IPCV'2010: International Conference on Image Processing, Computer Vision, and Pattern Recognition, Jul 2010, Las Vegas, Nevada, United States. pp.701-707. ⟨lirmm-00993594⟩

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