Context - dependent color segmentation for Aibo robots

Abstract

Color segmentation is a key step in any color-based robot vision system. The main factors that affect the performance of the segmentation process are the variable lighting conditions of the environment, the natural overlap between the color classes in the color space, and the distortion produced in the images by the movement of the camera and the robot. In the context of the robot soccer championship RoboCup, several segmentation approaches have been proposed, most of them based on an off-line calibration phase where a look-up table is generated for the on-line system operation. The here proposed approach employs ambiguous colors as a way of including in the calibration process the natural uncertainness of the problem. Thus, the color segmentation result is not completely defined in the calibration phase. During on-line operation a mode filter is employed for incorporating context information in the discrimination of the final class of the colors. Successful results of the application of the proposed dynamic color segmentation methodology are shown in the context of the RoboCup four-legged league