A model based approach to lane detection and lane positioning using OpenCV

Typ
Examensarbete på grundnivå
Program
Publicerad
2017
Författare
Posch, Daniel
Rask, Jesper
Modellbyggare
Tidskriftstitel
ISSN
Volymtitel
Utgivare
Sammanfattning
The aim of this thesis was to implement and develop a computer vision based method that would play a important part in the implementation of an autonomous RC car. In particular this thesis provides the initial steps of image pre-processing, an algorithm for lane detection, position identification and a communication model. The study was preformed with two main goals. The first goal consists of an investigation of a suitable algorithm to efficiently detect specific information from an image, to be able to act in a way based on the extracted data. The second goal was to determine what camera specifications are needed for the chosen algorithm. Using different approaches of algorithms for detecting a path between lanes, this thesis present an implementation of the B-snake model. The program is evaluated in the Udacity game simulator, as well as on real hardware with challenging benchmarks such as lanes with hard curvature, high speed and noisy environments. The program performed well in different environments together with a limited speed. However lanes with curvature which exceeds 25 degrees has to be further developed in the future.
Beskrivning
Ämne/nyckelord
Informations- och kommunikationsteknik, Data- och informationsvetenskap, Information & Communication Technology, Computer and Information Science
Citation
Arkitekt (konstruktör)
Geografisk plats
Byggnad (typ)
Byggår
Modelltyp
Skala
Teknik / material