Abstract
Autonomous detection of crop rows based on adaptive multi-ROI in maize fields
Highlights
The progress of agricultural science is the most important indicator to measure the productivity of modern agriculture[1]
To address the problem, considered the algorithms proposed by previous scholars, this paper proposed a crop rows detection method based on multi-region of interest (ROI)
After the navigation line was extracted, detection lines of crop rows were again extracted in multi-ROI by the least squares method
Summary
The progress of agricultural science is the most important indicator to measure the productivity of modern agriculture[1]. Scholars have conducted various studies on intelligent operating systems for agricultural machinery. Agricultural navigation technology usually relies on a global positioning system (GPS) for autonomous driving of agricultural machinery in the field[5,6,7]. In maize fields, GPS-based navigation systems can hardly ensure that vehicles travel between crop ridges, resulting in a high rate of seedling damage from wheels. The field navigation of agricultural vehicles based on machine vision relies mainly on the development of crop rows detection algorithms[10]. With the crop rows detection based on machine vision, it is possible to ensure that the vehicles travel between the crop ridges to avoid crushing seedlings
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