Using Color and Shape Analysis for Boundary Line Extraction in Autonomous Vehicle Applications

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dc.contributor.authorGopinath, Sudhiren
dc.contributor.committeechairReinholtz, Charles F.en
dc.contributor.committeememberKachroo, Pushkinen
dc.contributor.committeememberSaunders, William R.en
dc.contributor.departmentMechanical Engineeringen
dc.date.accessioned2014-03-14T20:45:15Zen
dc.date.adate2003-09-15en
dc.date.available2014-03-14T20:45:15Zen
dc.date.issued2002-12-20en
dc.date.rdate2003-09-15en
dc.date.sdate2003-09-11en
dc.description.abstractAutonomous vehicles are the subject of intense research because they are a safe and convenient alternative to present-day vehicles. Human drivers base their navigational decisions primarily on visual information and researchers have been attempting to use computers to do the same. The current challenge in using computer vision lies not in the collection or transmission of visual data, but in the perception of visual data to extract from it useful information. The focus of this thesis is on the use of computer vision to navigate an autonomous vehicle that will participate in the Intelligent Ground Vehicle Competition (IGVC.) This document starts with a description of the IGVC and the software design of an autonomous vehicle. This thesis then focuses on the weakest link in the system - the computer vision module. Vehicles at the IGVC are expected to autonomously navigate an obstacle course. Competing vehicles need to recognize and stay between lines painted on grass or pavement. The research presented in this document describes two methods used for boundary line extraction: color-based object extraction, and shape analysis for line recognition. This is the first time a combination of these methods is being applied to the problem of line recognition in the context of the IGVC. The most significant contribution of this work is a method for extracting lines in a binary image even when the line is attached to a shape that is not a line. Novel methods have been used to simplify camera calibration, and for perspective correction of the image. The results give promise of vastly improved autonomous vehicle performance.en
dc.description.degreeMaster of Scienceen
dc.identifier.otheretd-09112003-021801en
dc.identifier.sourceurlhttp://scholar.lib.vt.edu/theses/available/etd-09112003-021801/en
dc.identifier.urihttp://hdl.handle.net/10919/35015en
dc.publisherVirginia Techen
dc.relation.haspartThesisSudhir003Final.pdfen
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.subjectBinary Image Analysisen
dc.subjectComputer Visionen
dc.subjectAutonomous Vehiclesen
dc.subjectLine Recognitionen
dc.subjectColor Extractionen
dc.subjectShape Analysisen
dc.subjectMobile Robotsen
dc.titleUsing Color and Shape Analysis for Boundary Line Extraction in Autonomous Vehicle Applicationsen
dc.typeThesisen
thesis.degree.disciplineMechanical Engineeringen
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen
thesis.degree.levelmastersen
thesis.degree.nameMaster of Scienceen
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