IEEE Trans Image Process - Interval-valued fuzzy sets applied to stereo matching of color images.

Tópicos

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Resumo

Stereo matching problem attempts to find corresponding locations between pairs of displaced images of the same scene. Correspondence estimation between pixels suffers from occlusions, noise, and bias. This paper introduces a novel approach to represent images by means of interval-valued fuzzy sets. These sets allow one to overcome the uncertainty due to the aforementioned problems. The aim is to take advantage of the new representation to develop a stereo matching algorithm. The interval-valued fuzzification process for images that is proposed here is based on image segmentation. Interval-valued fuzzy similarities are introduced to compare windows whose pixels are represented by intervals. To make use of color information, the similarities of the RGB channels were aggregated using the luminance formula. The experimental analysis makes a comparison with other methods. The new representation that is proposed together with the new similarity measure show a better overall behavior, providing more accurate correspondences, mainly near depth discontinuities and for images with a large amount of color.

Resumo Limpo

stereo match problem attempt find correspond locat pair displac imag scene correspond estim pixel suffer occlus nois bias paper introduc novel approach repres imag mean intervalvalu fuzzi set set allow one overcom uncertainti due aforement problem aim take advantag new represent develop stereo match algorithm intervalvalu fuzzif process imag propos base imag segment intervalvalu fuzzi similar introduc compar window whose pixel repres interv make use color inform similar rgb channel aggreg use lumin formula experiment analysi make comparison method new represent propos togeth new similar measur show better overal behavior provid accur correspond main near depth discontinu imag larg amount color

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