Abstract
An early stage in image understanding using colour involves recognizing the colour of target objects by looking at individual pixels. However, even when, to the human eye, the colours in the image are distinct, it is a challenge for machine vision to reliably recognize the whole object from colour alone, due to variations in lighting and other environmental issues. In this paper, we investigate the use of decision trees as a basis for recognizing colour. We also investigate the use of colour space transforms as a way of eliminating variations due to lighting.
Part of this work was supported by CSIRO Mathematical and Information Sciences, Australia
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Brusey, J., Padgham, L. (2000). Techniques for Obtaining Robust, Real-Time, Colour-Based Vision for Robotics. In: Veloso, M., Pagello, E., Kitano, H. (eds) RoboCup-99: Robot Soccer World Cup III. RoboCup 1999. Lecture Notes in Computer Science(), vol 1856. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45327-X_19
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DOI: https://doi.org/10.1007/3-540-45327-X_19
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