Date of Graduation
Bachelor of Science in Computer Science
Computer Science and Computer Engineering
Committee Member/Second Reader
Le, Ngan T. H.
OpenCV, and Computer Vision in general, has been a Computer Science topic that has interested me for a long time while completing my Bachelor’s degree at the University of Arkansas. As a result of this, I ended up choosing to utilize OpenCV in order to complete the task of detecting road-lines and mapping roads when given a wide variety of images. The purpose of my Honors research and this thesis is to detail the process of creating an algorithm to detect the road-lines such that the results are effective and instantaneous, as well as detail how Computer Vision can be applied to abstract ideas of detecting objects near the same level that a human would.
The detection and mapping of road-lines was executed via an algorithm that incorporated several different parameters and specifications, all of which went through many iterations before being somewhat optimized to the state it is currently in. Furthermore, the thresholding algorithm that I developed would allow and adapt for inputting many different images, as well as active video functionality. This algorithm manually reads through every pixel in the image/frames of a video and detects row patterns by preforming a multitude of custom mathematical calculations on the BGR color values of the image/frames, resulting in the filling of the bounds of the lines by row and thus detailing where the road is.
Thresholding, Computer Vision, OpenCV Pixel Operations, Video Processing
Lyle, J. C. (2023). Developing Detection and Mapping of Roads within Various Forms of Media Using OpenCV. Computer Science and Computer Engineering Undergraduate Honors Theses Retrieved from https://scholarworks.uark.edu/csceuht/128