College of Electrical Engineering, Guangxi University, Nanning 530004, China.
State Grid Anhui Electric Power Co., Ltd., Feidong County Power Supply Company, Hefei 231600, China.
Comput Intell Neurosci. 2022 Sep 27;2022:3083647. doi: 10.1155/2022/3083647. eCollection 2022.
This study used Kinect V2 sensor to collect the three-dimensional point cloud data of banana pseudostem and developed an automatic measurement method of banana pseudostem width. The banana plant was selected as the research object in a banana plantation in Fusui, Guangxi. The mobile measurement of banana pseudostem was carried out at a distance of 1 m from the banana plant using the field operation platform with Kinect V2 as the collection equipment. To eliminate the background data and improve the processing speed, a cascade classifier was used to recognize banana pseudostems from the depth image, extract the region of interest (ROI), and transform the ROI into a color point cloud combined with the color image; secondly, the point cloud was sparse by down-sampling; then, the point cloud noise was removed according to the classification of large-scale and small-scale noise; finally, the stem point cloud was segmented along the -axis, and the difference between the maximum and minimum values in the -axis direction of each segment was calculated as its horizontal width. The center point of each segment point cloud was used to fit the slope of the stem centerline, and the average horizontal width was corrected to the stem diameter. The test results show that the average measurement error is only 2.7 mm, the average relative error was 1.34%, and the measurement time is only about 300 ms. It could provide an effective solution for the automatic and rapid measurement of stem width of banana plants and other similar plants.
本研究使用 Kinect V2 传感器采集香蕉假茎的三维点云数据，并开发了一种香蕉假茎宽度的自动测量方法。选择广西扶绥的香蕉种植园中的香蕉植株作为研究对象。使用以 Kinect V2 为采集设备的田间作业平台，在距离香蕉植株 1 m 的地方进行香蕉假茎的移动测量。为了消除背景数据并提高处理速度，使用级联分类器从深度图像中识别香蕉假茎，提取感兴趣区域（ROI），并结合彩色图像将 ROI 转换为彩色点云；其次，通过下采样对点云进行稀疏化；然后，根据大、小噪声分类去除点云噪声；最后，沿-z 轴对茎点云进行分割，并计算每个分段在-z 方向上的最大值和最小值之间的差值作为其水平宽度。每个分段点云的中心点用于拟合茎中心线的斜率，并校正平均水平宽度为茎直径。测试结果表明，平均测量误差仅为 2.7mm，平均相对误差为 1.34%，测量时间仅约 300ms。它可以为香蕉植株和其他类似植物的茎宽自动快速测量提供有效的解决方案。
