融合图像边缘和区域特征的道路检测算法

Road detection algorithm using the edge and region features in images

利用图像分割技术对车载视频进行图像处理,提取道路信息,以用于智能车自动驾驶.首先,将彩色通道图像转换成灰度图像,并进行直方图均衡化和滤波预处理;然后,利用自定义差分算子和区域生长法,进一步对处理后的灰度图像进行分割,分别获得图像的边缘和区域特征.最后,结合区域和边缘分割的互补特性,提出一个融合两者信息的分割算法,对不同条件下获得的车载视频进行图像分割,实现道路检测.实验结果表明,所提出的方法能够获得边缘精确平滑、区域均匀的道路分割,而且算法具备较好的实时性和鲁棒性.

An image segmentation technology is presented to extract the road information from video images taken by a vehicle on-board camera,for the purpose of automatic driving of intelligent vehicles.First,color images are converted into gray-level images,w hich are further processed w ith histogram equalization and median filter.Then,a self-defined difference operator and a region grow ing method are proposed,respectively,to extract the edge and region object information from the preprocessed gray-level images.Finally,by a combination of the tw o methods,a new segmentation method is proposed through the use of the edge and region features,to realize the road detection from the vehicle video images obtained under various conditions.Experimental results show that more accurate edges and uniform regions can be achieved by the proposed segmentation approach,and it is fast and robust.