针对机器人彩色视觉系统的实时性要求，提出了一种基于YUV色彩空间的利用阈值向量来分割图象的识别方法，并改进了种子填充算法，从而明显减少了识别的计算量，并在保证识别精度的前提下，提高了处理速度.通过在 Miro Sot机器人足球系统上的应用，验证了此方法的有效性，而该方法与常用的基于 RGB颜色空间的方法进行比较的结果也证明，此方法确有明显的优越性.

Robot Soccer game is become popular recent years. The system combined with mechanic, electronic, control, computer, image process and etc. In order to win the game, the system must be more quick and more accuracy. Because vision sub-system is the first step of the whole system, its speed and accuracy are important to the whole systems speed and accuracy. Real-time segmentation is the first step in the color-vision system on the robot system. A color image segmentation method using improved seed-fill algorithm in YUV color space is introduced in this paper. The new method dramatically reduces the work of calculation, and speeds up the image processing. The result of comparing it with the old method based on RGB color space was showed in the paper. The second step of the vision sub-system is identification the color block that separated by the first step. A improved seed fill algorithm is used in the paper. The implementation on MiroSot Soccer Robot System shows that the new method is fast and accurate.