多颜色模型下的乒乓球快速检测与实时跟踪研究

乒乓球机器人视觉系统中的乒乓球检测主要有基于运动分析和基于单一颜色模型分割两种方法.基于运动分析的方法对运动背景干扰的鲁棒性较差，而基于单一颜色模型的分割方法会受到相近颜色及光照变化的干扰.为此，提出了多颜色模型下的乒乓球分割算法，结合RGB与HSV两种颜色模型的颜色表达特性提取出乒乓球区域，并利用质心法对乒乓球进行中心定位.在此基础上，提出基于前帧位置的感兴趣区域算法，对乒乓球进行实时跟踪.实验表明，该方法能够在复杂环境下对乒乓球进行快速精确定位，算法处理时间小于10 ms，定位误差小于20 mm，满足乒乓球机器人的击球需要.

Quick Detection and Real-Time Tracking for Table Tennis Ball Based on Multi-Color Models

The two major detection methods for table tennis ball by table tennis robot''s visual system are based on motion analysis or detection by single color models. The motion analysis methods have poor robustness in moving background, while the similar color and light intensity change will interfere the performance of detection methods based on single color model. A quick detection method based on multi-color models was proposed, the RGB color model and HSV color model are combined to extract the region of table tennis ball as a binary image, and the center of ball is positioned by calculating the barycenter. On this basis, Region Of Interest (ROI) technology based on previous frame position was proposed for real-time tracking. Experiments show that this method can accurate positioning table tennis ball in complex environment, the algorithm processing time is less than 10 ms, and positioning error is less than 20 mm. Its precision meets the demand of table tennis robot.