Shrestha, Rini2013-09-242013-09-242013-05https://hdl.handle.net/11299/157207University of Minnesota M.S. thesis. May 2013. Major:Electrical Engineering. Advisor: Dr.Jiann-Shiou Yang. 1 computer file (PDF); vi, 62 pages, appendix, p. 58-62.With the increasing number of vehicles on the road the number of accidents have also been increasing. Development of various techniques such as lane departure warning systems that helps drivers to assist in driving can help reduce the number of accidents significantly. In this thesis, we attempt to develop such lane departure warning system by estimating the vehicle's lateral position. The lateral position of vehicle can be known if the heading angle of the vehicle can be determined. Therefore, this study focuses on determining heading angle and works toward development of the lane departure warning system based on image processing techniques. An in-vehicle camera is used to capture the images of the road in real time. The system then uses homography on this front - view images of the road to remove the perspective effect and transform the images such that the obtained resulting images represent as if they were observed from the top. The histogram equalization is also applied to the images to increase the global contrast by spreading out the most frequent intensity values. Shi and Tomasi corner detection technique has been used to find significant features (corners) in the images and Lucas - Kanade optical flow to track those corners in following images. The heading angle, and thus the lateral displacement, is determined by relating these tracked corners. As part of the study, a number of road tests were conducted on different roads of Duluth, MN and the findings based on the road tests are discussed.en-USFeature selectionHeading angleHomographyImage processingOptical flowThesis or Dissertation