摘要
提出了根据高斯分布模型的自适应阈值分割方法,使用了基于形态学变换的二值图优化算法得到车道线边缘图.改进了概率霍夫变换,使其更能满足实际情况,从而换检测出车道线.实验表明了该方法可以有效检测出车道线,并且速度上得到了极大的提高.
Applied an adaptive threshold segmentation method based on Gaussian distribution model,then,image noise was filtered by morphological transformation and a map of lane edges was formed.Improved progressive probabilistic Hough transform to better meet the actual situation.This experiment suggested that this method can effectively detect lanes,also has an obvious advantage in detection rate.
出处
《微电子学与计算机》
CSCD
北大核心
2011年第10期177-180,共4页
Microelectronics & Computer
关键词
概率霍夫变换
车道线检测
智能车辆
图像处理
progressive probabilistic Hough transform
lane detection
intelligent vehicle
image processing
