【摘要】 为解决水果采摘机器人快速、准确识别目标问题,提出一种基于机器视觉的类球状水果识别方法。首先采用基于颜色归一化差的图像分割算法,将果实从背景中分割出来;然后利用单像素边缘跟踪算法提取果实边缘,并在跟踪过程中利用直线投影法剔除角点,使交叉边缘在角点处断开,提高遮挡情况下识别的准确性;最后通过最小二乘法检测圆形,识别果实。实验结果表明,算法处理中等大小的图像平均用时83.548ms,识别准确率达95%以上。算法快速、鲁棒,可以满足机器人实时作业要求。更多还原

【Abstract】 In order to solve the problem of fruit picking robot target identification,the paper put forward a novel method based on machine vision.Firstly,the fruits were segmented from background by the algorithm based on normalized color difference.Secondly,the fruit edges were extracted by the single pixel tracking algorithm and during tracking the corners were deleted by linear projection method.The crossed edges were broken off at the corner.It improved the accuracy of recognition in the case of occlusion.Lastly,circles were detected by least square method to identify fruits.The experimental results showed that it take 83.548 ms to process a medium size image averagely.Its accuracy is larger than 95%.The algorithm is fast and robust.It meets the real time requirement of picking robot.更多还原