机器视觉在幼苗自动移钵作业中的应用

该文提出了一套在自动幼苗移钵作业中用于幼苗生长状况检测的机器视觉系统。穴盘中幼苗的图像被采集和处理，识别出适合进行移钵的单元，用于自动幼苗移钵机的移钵作业。相邻单元的幼苗边缘重叠和叶片挤压会造成识别错误，在该研究中以番茄幼苗作为试验样本，使用基于形态学的分水岭算法处理来完成叶片边缘分割，提取每个穴孔中幼苗的叶片面积和叶片周长来确定适合进行移钵的单元。试验结果表明该机器视觉系统识别准确率达到了98%，应用于自动幼苗移钵机器人中可以很好地判断不同生长状况的秧苗生长质量。

Application of machine vision on automatic seedling transplanting

This paper presents a machine vision system for automatic seedling transplanting. To reduce transplanting time, image which seedling plants grow in tray was acquired and processed in order to identify the cells to be transplanted. Overlapping of the border seedlings and extruding leaves from neighboring cells always leads to identification failures. So a digital image processing algorithm based on morphological watersheds was developed to segment the border of leaves. The area and the perimeter of seedlings were extracted, by which whether the cell was suitable for transplanting could be determined. In this research, using tomato seedlings as samples, good identification rate for suitable seedling was obtained (98%). The result shows that this method can be used in various growing conditions of seedling, and this system can be used for automatic seedling transplanting robot.