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dc.contributor.authorMurad, Rodi
dc.description.abstractImage processing for object detection and decision making based on the observed remains a challenge today. As participants in the Intelligent Ground Vehicle Competition in 2018 and 2019, we were tasked to build an autonomous vehicle capable of maneuvering through a grassy course delineated with white lines and laid out with obstacles. To remain within the white line boundaries, we used OpenCV and Python for image processing and white line detection. To accomplish the task, we used image processing techniques such as image filtering, blurring, and edge detection. Although this algorithm was produced for the specific application of detection edges of white lines and obstacles found throughout the course, it can be used for the detection of edges of various objects for shape comparison for identification, as well as quality control of produced goods.en_US
dc.publisherNorth Dakota State Universityen_US
dc.rightsNDSU policy 190.6.2en_US
dc.titleImage Processing for White Line Detection in a Grassy Fielden_US
dc.typeThesisen_US
dc.typeVideoen_US
dc.date.accessioned2020-11-09T21:52:34Z
dc.date.available2020-11-09T21:52:34Z
dc.date.issued2019
dc.identifier.urihttps://hdl.handle.net/10365/31639
dc.identifier.orcid0000-0002-9149-8750
dc.rights.urihttps://www.ndsu.edu/fileadmin/policy/190.pdfen_US
ndsu.degreeMaster of Science (MS)en_US
ndsu.collegeEngineeringen_US
ndsu.departmentComputer Scienceen_US
ndsu.programComputer Scienceen_US
ndsu.advisorStraub, Jeremy


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