Crop rows detection in maize fields remains a challenging problem due to variation in illumination and weeds interference under field conditions. This study proposed an algorithm for detecting crop rows based on adaptive multi-region of interest (multi-ROI). First, the image was segmented into crop and soil and divided into several horizontally labeled strips. Feature points were located in the first image strip and initial ROI was determined. Then, the ROI window was shifted upward. For the next image strip, the operations for the previous strip were repeated until multiple ROIs were obtained. Finally, the least square method was carried out to extract navigation lines and detection lines in multi-ROI. The detection accuracy of the method was 95.3%. The average computation time was 240.8 ms. The results suggest that the proposed method has generally favorable performance and can meet the real-time and accuracy requirements for field navigation.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.