{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/geometrical-stem-detection-from-image-data","title":"Geometrical Stem Detection from Image Data for Precision Agriculture","arxiv_id":"1812.05415","date":"2018-12-13","proceeding":null,"authors":["F. Langer","L. Mandtler","A. Milioto","E. Palazzolo","C. Stachniss"],"abstract":"High efficiency in precision farming depends on accurate tools to perform\nweed detection and mapping of crops. This allows for precise removal of harmful\nweeds with a lower amount of pesticides, as well as increase of the harvest's\nyield by providing the farmer with valuable information. In this paper, we\naddress the problem of fully automatic stem detection from image data for this\npurpose. Our approach runs on mobile agricultural robots taking RGB images.\nAfter processing the images to obtain a vegetation mask, our approach separates\neach plant into its individual leaves and later estimates a precise stem\nposition. This allows an upstream mapping algorithm to add the high-resolution\nstem positions as a semantic aggregate to the global map of the robot, which\ncan be used for weeding and for analyzing crop statistics. We implemented our\napproach and thoroughly tested it on three different datasets with vegetation\nmasks and stem position ground truth. The experiments presented in this paper\nconclude that our module is able to detect leaves and estimate the stem's\nposition at a rate of 56 Hz on a single CPU. We furthermore provide the\nsoftware to the community.","url_abs":"http://arxiv.org/abs/1812.05415v1","url_pdf":"http://arxiv.org/pdf/1812.05415v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"geometrical-stem-detection-from-image-data","repo_url":"https://github.com/Photogrammetry-Robotics-Bonn/geometrical_stem_detection","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":null,"task_name":"CPU"},{"task_slug":null,"task_name":"Position"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}