基于计算机视觉高速智能车辆的道路识别
Based on Machine Vision Lane Detection For High Speed Intelligent Vehicle
本文研究了基于计算机视觉高速智能车辆的道路识别。通过对JLUIV-4智能高速车辆系统采集的图像进行中值滤波、边缘增强、最优阈值二值化，获得良好的梯度图像。根据道路特征采用Hough变换识别出道路边界。使用感兴趣区域，减少图像处理时间和提高道路识别的可靠性。JLUIV-4的高速导航实验表明，该种算法具有良好的实时性、可靠性和鲁棒性。
he paper presents a fast and robust approach of automatic lane detection for high speed intelligent vehicle. In order to obtain good gradient images, median filter, edge enhancement and optimal threshold are adopted to processing images taken by JLUIV-4 CCD camera. Lane edge is located according to it’s feature model through Hough transformation. By focusing on Area of Interest(AOI) processing time is dramatically reduced. Moreover, the reliability of lane detection is improved. The experimental result shows that this approach is of high efficiency , reliability and robustness on JLUIV-4.
游峰、崔高健、王荣本
公路运输工程自动化技术、自动化技术设备计算技术、计算机技术
计算机视觉智能车辆Hough变换道路检测.
computer visionintelligent vehicleHough transformationlane detection.
游峰,崔高健,王荣本.基于计算机视觉高速智能车辆的道路识别[EB/OL].(2004-03-16)[2025-08-02].http://www.paper.edu.cn/releasepaper/content/200403-123.点此复制
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