Next Article in Journal
Development of a Fingertip Glove Equipped with Magnetic Tracking Sensors
Next Article in Special Issue
Machine Learning Methods for Classifying Human Physical Activity from On-Body Accelerometers
Previous Article in Journal
Evaluation of Three Electronic Noses for Detecting Incipient Wood Decay
Previous Article in Special Issue
Improving the Response of Accelerometers for Automotive Applications by Using LMS Adaptive Filters: Part II
Article Menu

Export Article

Open AccessArticle
Sensors 2010, 10(2), 1093-1118;

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
View Full-Text   |   Download PDF [1148 KB, uploaded 21 June 2014]


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).

Share & Cite This Article

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.

Show more citation formats Show less citations formats

Related Articles

Article Metrics

Article Access Statistics



[Return to top]
Sensors EISSN 1424-8220 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top