IIUM Repository

Road lane tracking based on monocular vision

Al-Amoodi, Abdullah and Balfaqih, Omar and Htike@Muhammad Yusof, Zaw Zaw (2015) Road lane tracking based on monocular vision. International Journal of Applied Engineering Research, 10 (8). pp. 19647-19658. ISSN 0973-4562

[img] PDF
Restricted to Repository staff only

Download (692kB) | Request a copy
[img] PDF (SCOPUS) - Published Version
Restricted to Repository staff only

Download (480kB) | Request a copy


Lane tracking and detection is a complex problem due to the versatility of road conditions in which the road stream of images is analyzed. In this paper, an algorithm was developed to obtain a robust real-time lane tracking under a sudden appearance of obstacles such as vehicles and shadows. The method starts with applying Gaussian filter to grey scale images. Then, ROI is defined by finding the lowest mean of all rows in the image. Canny edge detector followed by Hough Transform are applied to the ROI to acquire lines. The information of lines in a sequence of frames are stored to predict the lane position. This method was tested on 1700 frames in different situations and proved its robustness.

Item Type: Article (Journal)
Additional Information: 6919/43041
Uncontrolled Keywords: Lane detection, Hough Transform, canny edge detection
Subjects: A General Works > AI Indexes (General)
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button): Kulliyyah of Engineering
Depositing User: Mr. Zaw Zaw Htike
Date Deposited: 26 May 2015 09:14
Last Modified: 07 Nov 2017 16:07
URI: http://irep.iium.edu.my/id/eprint/43041

Actions (login required)

View Item View Item


Downloads per month over past year