Color learning on a mobile robot: towards full autonomy under changing illumination
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Towards illumination invariance in the legged league
RoboCup 2004
Analysis of document snippets as a basis for reconstruction
VAST'09 Proceedings of the 10th International conference on Virtual Reality, Archaeology and Cultural Heritage
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In the colour coded environment of the RoboCup 4 Legged League it is crucial to extract as much colour information as possible from an image without error. To do this requires hours of manual YUV pixel mapping and testing to ensure robustness under all possible lighting conditions. The YUV colour space is a very convenient standard for transmission of video data, but for colour classification and segmentation it suffers from being non-intuitive and sensitive to changes in lighting. Alternatively, colour classification principles can be applied in an HSI colour space; one of the convenient characteristics of the HSI colour space is that the hue value, H, represents the colour wavelength information. From this concept it is easier to separate and label colour regions in an automated process as the theoretical hue and colour wavelength relationship is known. By fitting a Gaussian model using mixtures to HSI histograms we can generate boundaries of colour classes in HSI colour space.