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Representing images by means of interval-valued fuzzy sets. Application to stereo matching
conference contribution
posted on 2011-01-01, 00:00 authored by M Galar, E Barrenechea, J Fernandez, H Bustince, Gleb BeliakovGleb BeliakovStereo matching tries to find correspondences between locations in a pair of displaced images of the same scene in order to extract the underlying depth information. Pixel correspondence estimation suffers from occlusions, noise or bias. In this work, we introduce a novel approach to represent images by means of interval-valued fuzzy sets to overcome the uncertainty due to the above mentioned problems. Our aim is to take advantage of this representation in the stereo matching algorithm. The image interval-valued fuzzification process that we propose is based on image segmentation in a different way to the common use of segmentation in stereo vision. We introduce interval-valued fuzzy similarities to compare windows whose pixels are represented by intervals. In the experimental analysis we show the goodness of this representation in the stereo matching problem. The new representation together with the new similarity measure that we introduce shows a better overall behavior with respect to other very well-known methods.
History
Event
Symposium on Advances in Type-2 Fuzzy Logic Systems (1st : 2011 : Paris, France)Pagination
134 - 141Publisher
IEEELocation
Paris, FrancePlace of publication
[Paris, France]Start date
2011-04-11End date
2011-04-15ISBN-13
9781612840772ISBN-10
1612840779Language
engPublication classification
E1 Full written paper - refereedCopyright notice
2011, IEEETitle of proceedings
T2FUZZ 2011 : IEEE Symposium on Advances in Type-2 Fuzzy Logic SystemsUsage metrics
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