Lane detection algorithm based on open source computer vision

Every year, there is a significant increase in the number of road accidents on both cars and trucks alike. Such accidents may have been triggered by the human error of drivers, poor driving conditions, or the mechanical failure of the vehicle's components. One way of decreasing the occurrence o...

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Bibliographic Details
Main Authors: Dorado, Patrick Vincent E., Huang, Ainsley P., Paguio, Jermaine Avion A.
Format: text
Language:English
Published: Animo Repository 2009
Subjects:
Online Access:https://animorepository.dlsu.edu.ph/etd_bachelors/6269
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Institution: De La Salle University
Language: English
Description
Summary:Every year, there is a significant increase in the number of road accidents on both cars and trucks alike. Such accidents may have been triggered by the human error of drivers, poor driving conditions, or the mechanical failure of the vehicle's components. One way of decreasing the occurrence of such accidents is by lessening, if not eliminating, the cause of human errors while driving. In this paper, a machine vision system is introduced, which enables the computer to detect lanes using an algorithm based on the Open Source Computer Vision libraries. The system produced, compared to those out in the market, is developed using low cost materials, gadgets, and software that are freely available in the market. It is capable of detecting and tracing the different kinds of road lanes such as straight, broken, and continuous. Also, it is capable of producing a robust and accurate detection of the said lanes in various road conditions such as daytime, night time, rainy, and overcast weather. The result of the said detection is displayed to the user using a graphical user interface developed using the same low cost programs and software. The accuracy of the system is then gauged by the discrepancy of the projected lane of the algorithm, with respect to the original lane to be detected. A higher accuracy is then given to the system if the disparity of the projected and the original lane is within the bounds of an acceptable margin. With the development of such a system, the authors wish for the eventual automation of automobiles with the use of the developed low cost lane detection system.