用图像识别土壤与秸秆，精准测量覆盖土层的地面距离。
Image-based ground distance detection for crop-residue-covered soil
- 结合深度相机与彩色相机，通过图像分割区分土壤和秸秆区域。
- 测量误差控制在±3mm内，满足实时作业需求。
- 适合保护性耕作中精量播种，也可用于移栽、翻耕等场景。
保护性农业采用作物残茬覆盖土壤，有助于改善土壤健康并节水。但其关键挑战在于：残茬覆盖下难以精确控制播种深度，因现有激光、超声或机械位移传感器无法区分测量值来自残茬还是土壤。本文提出一种基于图像的地面距离检测方法，利用3D相机与RGB相机同步获取深度图与彩色图。彩色图用于区分残茬与土壤区域，生成掩码图像；该掩码应用于深度图，仅保留土壤区域的深度信息以计算地面距离，残茬区域则被排除。实验表明，该方法可实现实时应用，测量误差在±3mm以内，适用于保护性农业农机精量播种，亦可用于移栽、耕作等对深度控制有要求的场景。
原文摘要 · Abstract (English)
Conservation agriculture features a soil surface covered with crop residues, which brings benefits of improving soil health and saving water. However, one significant challenge in conservation agriculture lies in precisely controlling the seeding depth on the soil covered with crop residues. This is constrained by the lack of ground distance information, since current distance measurement techniques, like laser, ultrasonic, or mechanical displacement sensors, are incapable of differentiating whether the distance information comes from the residue or the soil. This paper presents an image-based method to get the ground distance information for the crop-residues-covered soil. This method is performed with 3D camera and RGB camera, obtaining depth image and color image at the same time. The color image is used to distinguish the different areas of residues and soil and finally generates a mask image. The mask image is applied to the depth image so that only the soil area depth information can be used to calculate the ground distance, and residue areas can be recognized and excluded from ground distance detection. Experimentation shows that this distance measurement method is feasible for real-time implementation, and the measurement error is within plus or minus 3mm. It can be applied in conservation agriculture machinery for precision depth seeding, as well as other depth-control-demanding applications like transplant or tillage.
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