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

Most 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 en...

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Bibliographic Details
Main Authors: Espinola, A., Romay, A., Baidyk, T., Kussul, E.
Format: Conference Proceeding
Language:English
Subjects:
Calibration
Cameras
Correlation
Image color analysis
Image segmentation
Lighting
Robots
Online Access:Request full text
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Summary:Most 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.
DOI:10.1109/ROBIO.2011.6181339