In this paper we propose an approach to color classification and image segmentation in non-stationary environments. Our goal is to cope with changing illumination condition by on-line adapting both the parametric color model and its structure/complexity. Other authors used parametric statistics to model color distribution in segmentation and tracking problems, but with a fixed complexity model. Our approach is able to on-line adapt also the complexity of the model, to cope with large variations in the scene illumination and color temperature.
Sorrenti, D., Matteucci, M., Bosisio, D., Anzani, F. (2006). On-Line Color Calibration in Non-Stationary Environments. In RoboCup 2005: Robot Soccer World Cup IX Conference proceedings (pp.396-407). Springer Verlag [10.1007/11780519_35].
On-Line Color Calibration in Non-Stationary Environments
Sorrenti, DG;
2006
Abstract
In this paper we propose an approach to color classification and image segmentation in non-stationary environments. Our goal is to cope with changing illumination condition by on-line adapting both the parametric color model and its structure/complexity. Other authors used parametric statistics to model color distribution in segmentation and tracking problems, but with a fixed complexity model. Our approach is able to on-line adapt also the complexity of the model, to cope with large variations in the scene illumination and color temperature.
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