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  4. Image Processing Techniques for Lane-Related Information Extraction and Multi-Vehicle Detection in Intelligent Highway Vehicles
 
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Image Processing Techniques for Lane-Related Information Extraction and Multi-Vehicle Detection in Intelligent Highway Vehicles

Resource
International Journal of Automotive Technology 8 (4): 513-520
Journal
International Journal of Automotive Technology
Journal Volume
8
Journal Issue
4
Pages
513-520
Date Issued
2007-08
Date
2007-08
Author(s)
Wu, Yao-Jan
Lian, Feng-Li  
Huang, Chun-Po
Chang, Tang-Hsien
URI
http://www.scopus.com/inward/record.url?eid=2-s2.0-36049004302&partnerID=MN8TOARS
http://ntur.lib.ntu.edu.tw//handle/246246/132932
http://ntur.lib.ntu.edu.tw/bitstream/246246/132932/1/index.html
Abstract
In this paper, we propose an approach to identify the driving environment for intelligent highway vehicles by means of image processing and computer vision techniques. The proposed approach mainly consists of two consecutive computational steps. The first step is the lane marking detection, which is used to identify the location of the host vehicle and road geometry. In this step, related standard image processing techniques are adapted for lane-related information. In the second step, by using the output from the first step, a four-stage algorithm for vehicle detection is proposed to provide information on the relative position and speed between the host vehicle and each preceding vehicle. The proposed approach has been validated in several real-world scenarios. Herein, experimental results indicate low false alarm and low false dismissal and have demonstrated the robustness of the proposed detection approach.
Subjects
Driving environment identification
Image processing
Computer vision
Lane-related information
Vehicle detection and tracking
Type
journal article
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