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Sensors 2010, 10(2), 1093-1118; doi:10.3390/100201093

Using Fuzzy Logic to Enhance Stereo Matching in Multiresolution Images

DCA-CT-UFRN, Campus Universitário, Lagoa Nova, Universidade Federal do Rio Grande do Norte, 59072-970 Natal RN, Brazil
Instituto de Computação, LCCV & CPMAT, Universidade Federal de Alagoas, BR 104 Norte km 97, 57072-970 Maceió AL, Brazil
Author to whom correspondence should be addressed.
Received: 10 December 2009 / Revised: 14 January 2010 / Accepted: 18 January 2010 / Published: 29 January 2010


Stereo matching is an open problem in Computer Vision, for which local features are extracted to identify corresponding points in pairs of images. The results are heavily dependent on the initial steps. We apply image decomposition in multiresolution levels, for reducing the search space, computational time, and errors. We propose a solution to the problem of how deep (coarse) should the stereo measures start, trading between error minimization and time consumption, by starting stereo calculation at varying resolution levels, for each pixel, according to fuzzy decisions. Our heuristic enhances the overall execution time since it only employs deeper resolution levels when strictly necessary. It also reduces errors because it measures similarity between windows with enough details. We also compare our algorithm with a very fast multi-resolution approach, and one based on fuzzy logic. Our algorithm performs faster and/or better than all those approaches, becoming, thus, a good candidate for robotic vision applications. We also discuss the system architecture that efficiently implements our solution. View Full-Text
Keywords: image analysis; fuzzy rules; multiresolution; sensor configuration; stereo matching; vision image analysis; fuzzy rules; multiresolution; sensor configuration; stereo matching; vision

This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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MDPI and ACS Style

Medeiros, M.D.; Gonçalves, L.M.G.; Frery, A.C. Using Fuzzy Logic to Enhance Stereo Matching in Multiresolution Images. Sensors 2010, 10, 1093-1118.

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