哈尔滨工程大学学报2011，Vol.32Issue(3)：334-339,6.DOI:10.3969/j.issn.1006-7043.2011.03.012
基于单目视觉的非结构化道路检测与跟踪
Unstructured road detection and tracking based on monocular vision
摘要
Abstract
To prevent an intelligent vehicle from departing from its lane in vision-based navigation, a method based on monocular vision was proposed to detect a road boundary. First, the original image was segmented into the road and non-road regions by using the Otsu adaptive threshold segmentation algorithm. Subsequently, the Canny edges were filtered so that certain complicated edges in the image could be eliminated and certain weak road boundaries could be preserved simultaneously. Finally, the Hough lines detected and tracked by the Monte Carlo method were represented by the length, average gradient amplitude, distance, and orientation of the line. Also, the adopted Monte Carlo method would be able to evaluate whether or not the Hough lines belong to certain road boundaries and therefore regard the Hough line having the maximum weight as the optimum road boundary. Experiments indicate that the method can not only overcome negative influences from road flaws, shadows, changes in illumination, and water stains while spending on average only 45ms processing each frame, but also meet the requirements of robustness, real-time, and accuracy.关键词
道路检测/蒙特卡罗方法/阈值分割/边缘检测/智能车辆Key words
road detection/ Monte Carlo method/ threshold segmentation/ edge detection/ intelligent vehicle分类
信息技术与安全科学引用本文复制引用
王燕清,陈德运,石朝侠..基于单目视觉的非结构化道路检测与跟踪[J].哈尔滨工程大学学报,2011,32(3):334-339,6.基金项目
黑龙江省教育厅科学技术研究资助项目(11541040 （）
11541050) （）
哈尔滨市青年科技创新人才基金资助项目(2008RFQXG067). （2008RFQXG067）
