【摘要】 从摄像机标定、图像获取、双目校正、立体匹配、深度计算等方面研究多种农田障碍物检测方法,分别用Bouguet算法进行立体校正、用区域匹配方法获取视差图、用三角测量方法计算障碍物的深度,获取了不同环境下的5种障碍物及其位置信息,并使用计算机视觉函数库OpenCV,提高了算法的实时性。试验表明:障碍物与摄像机的距离小于2 000 mm时,准确识别率在96%以上,深度的绝对误差在±30 mm内(即相对误差在1.5%以下),且完成一次障碍物检测的时间小于100 ms。更多还原

【Abstract】 Camera calibration,image acquisition,stereo rectification,stereo match and depth calculation were developed to research a detection method of various obstacles in farmland by using the methods such as Bouguet algorithm,area match,and triangulation and so on.As a result,five different obstacles and their position information in different environments were got,and open computer vision library OpenCV was used to improve the real time property.The experiment showed that the accuracy rate of the obstacle detection reached 96% and the absolute error of depth was maintained within ±30 mm(under 1.5% of the relative error) when the depth was less than 2 000 mm,and it takes less than 100 ms to finish a obstacle detection.更多还原