基于图像的作物残茬覆盖土壤地面距离检测
Image-based ground distance detection for crop-residue-covered soil
AI总结：
针对保护性农业中残茬覆盖土壤播种深度难以精确控制的问题，提出一种基于3D和RGB图像融合的地面距离检测方法，通过生成掩膜排除残茬区域干扰，实现误差正负3mm内的实时测量。
摘要：
保护性农业的土壤表面覆盖着作物残茬，这带来了改善土壤健康和节约用水的好处。然而，保护性农业面临的一个重大挑战在于精确控制覆盖有作物残茬的土壤上的播种深度。这受到缺乏地面距离信息的限制，因为目前的距离测量技术，如激光、超声波或机械位移传感器，无法区分距离信息是来自残茬还是土壤。本文提出了一种基于图像的方法来获取作物残茬覆盖土壤的地面距离信息。该方法使用3D相机和RGB相机执行，同时获取深度图像和彩色图像。彩色图像用于区分残茬和土壤的不同区域，并最终生成掩膜图像。该掩膜图像应用于深度图像，使得只有土壤区域的深度信息可用于计算地面距离，而残茬区域可以被识别并从地面距离检测中排除。实验表明，这种距离测量方法适用于实时实现，测量误差在正负3mm以内。它可以应用于保护性农业机械进行精密深度播种，以及其他需要深度控制的应用，如移栽或耕作。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
