Robust vision system to illumination changes in a color-dependent task

dc.contributor.authorAndrés Espínola
dc.contributor.authorAlberto Romay
dc.contributor.authorTatiana Baidyk
dc.contributor.authorErnst Kussul
dc.coverage.spatialBolivia
dc.date.accessioned2026-03-22T15:11:56Z
dc.date.available2026-03-22T15:11:56Z
dc.date.issued2011
dc.descriptionCitaciones: 4
dc.description.abstractMost computer vision tasks are strongly sensitive to illumination changes. This is the case of RoboCup competitions, being color dependent tasks, they require a robust color-based segmentation method of the image for object recognition. It is difficult to achieve a constant illumination in a work environment that is subject to day light changes. This is why camera parameters calibration such as exposure time must be robust enough to reduce the impact in the output images. A result comparison on the segmentation of images is made in three different color spaces, RGB, HSV, and YCrCb. We researched their connection with changes in lighting condition and select one of them that have less error for those environments. We introduce a fuzzy calibration method of the camera exposure time parameter, by histograms correlation. The calibrations results give an approximate value of the correct parameter to be modified in the camera in order to avoid affecting the thresholds of segmentation in the color recognition task.
dc.identifier.doi10.1109/robio.2011.6181339
dc.identifier.urihttps://doi.org/10.1109/robio.2011.6181339
dc.identifier.urihttps://andeanlibrary.org/handle/123456789/50958
dc.language.isoen
dc.sourceUniversidad Nacional Autónoma de México
dc.subjectArtificial intelligence
dc.subjectComputer vision
dc.subjectComputer science
dc.subjectHSL and HSV
dc.subjectRGB color model
dc.subjectColor normalization
dc.subjectColor histogram
dc.subjectSegmentation
dc.subjectHistogram
dc.subjectCalibration
dc.titleRobust vision system to illumination changes in a color-dependent task
dc.typearticle

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