The presence of weeds undermines the accurate algorithmic detection of navigation lines in cornfields, which plays a pivotal navigational role in the operation of intelligent agricultural machinery for tasks such as weeding and spraying. A method was proposed for extracting navigation lines by using the composite locations of the root and stalk of corn in the 6th- to 14th-leaf stages growing in a complex environment. The positional and area features were first used to eliminate the interference regions and obtain the root locations. The white pixel percentage index was used to filter the line segments obtained through the Hough transform and thereby determine the stalk locations. Experiments showed that the navigation lines were detected at an accuracy of 93.8%, an improvement of 10.2% over that achieved using conventional methods.

杂草的存在破坏了玉米田中导航线的精确算法检测，这在智能农业机械的除草和喷洒任务中起着至关重要的导航作用。提出了一种在复杂环境中生长的玉米的第6至第14叶阶段利用玉米根和茎的复合位置提取导航线的方法。位置和区域特征首先用于消除干扰区域并获得根位置。白色像素百分比指数用于过滤通过霍夫变换获得的线段，从而确定茎的位置。实验表明，检测到的导航线的准确度为93.8％，比传统方法提高了10.2％。