The road line detection is very important in vision navigation system of intelligent vehicle. The lane line detection should not be ignored in independence navigation.
在智能车辆的视觉导航系统中，车道线的检测有极其重要的作用，车道线的检测对于自主驾驶安全是不可忽视的。
A high speed lane detection method that satisfies the safety requirements of outdoor mobile robots was developed based on the segment-line road model and augmented transition networks (ATN).
为了满足室外移动机器人高速安全行驶的要求，提出了一种基于分段直线模型和增强型状态转移网络(atn)的车道识别方法。
This paper presents an algorithm combining scan line and region-growing method based on video images analysis, in which lane-marking recognition and driving deviation detection are realized.
为了实时检测到行车偏移信息，提出了一种基于扫描线与区域生长相结合的视频图像分析算法，从而实现了多种道路车道标线和行车偏移的自动检测。
This paper presents an algorithm combining scan line and region-growing method based on video images analysis, in which lane-marking recognition and driving deviation detection are realized.
为了实时检测到行车偏移信息，提出了一种基于扫描线与区域生长相结合的视频图像分析算法，从而实现了多种道路车道标线和行车偏移的自动检测。
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