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Journal of Sensors
Volume 2016, Article ID 4058093, 13 pages
Research Article

A Precise Lane Detection Algorithm Based on Top View Image Transformation and Least-Square Approaches

School of Mechanical and Automotive Engineering, Kunsan National University, Gunsan, Jeollabuk 573-701, Republic of Korea

Received 19 February 2015; Revised 21 June 2015; Accepted 23 June 2015

Academic Editor: Marco Listanti

Copyright © 2016 Byambaa Dorj and Deok Jin Lee. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


The next promising key issue of the automobile development is a self-driving technique. One of the challenges for intelligent self-driving includes a lane-detecting and lane-keeping capability for advanced driver assistance systems. This paper introduces an efficient and lane detection method designed based on top view image transformation that converts an image from a front view to a top view space. After the top view image transformation, a Hough transformation technique is integrated by using a parabolic model of a curved lane in order to estimate a parametric model of the lane in the top view space. The parameters of the parabolic model are estimated by utilizing a least-square approach. The experimental results show that the newly proposed lane detection method with the top view transformation is very effective in estimating a sharp and curved lane leading to a precise self-driving capability.