Research Article | OPEN ACCESS
A Night Time Application for a Real-Time Vehicle Detection Algorithm Based on Computer Vision
Shifu Zhou, Jianxiong Li, Zhenqian Shen and Liu Ying
School of Electronics and Information Engineering, Tianjin Polytechnic University,
Tianjin 300387, China
Research Journal of Applied Sciences, Engineering and Technology 2013 10:3037-3043
Received: September 27, 2012 | Accepted: November 11, 2012 | Published: March 25, 2013
Abstract
Vehicle detection technology is the key technology of intelligent transportation systems, attracting the attention of many researchers. Although much literature has been published concerning daytime vehicle detection, little has been published concerning nighttime vehicle detection. In this study, a nighttime vehicle detection algorithm, consisting of headlight segmentation, headlight pairing and headlight tracking, is proposed. First, the pixels of the headlights are segmented in nighttime traffic images, through the use of the thresholding method. Then the pixels of the headlights are grouped and labeled, to analyze the characteristics of related components, such as area, location and size. Headlights are paired based on their location and size and then tracked via a tracking procedure designed to detect vehicles. Vehicles with only one headlight or those with three or four headlights are also detected. Experimental results show that the proposed algorithm is robust and effective in detecting vehicles in nighttime traffic.
Keywords:
Headlights pairing, headlights tracking, intelligent transportation system, nighttime surveillance,
Competing interests
The authors have no competing interests.
Open Access Policy
This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
Copyright
The authors have no competing interests.
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ISSN (Online): 2040-7467
ISSN (Print): 2040-7459 |
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