基于纹理特征的非结构化道路分割算法

Segmentation algorithm of unstructured road based on texture feature

为了提取出智能车在视觉导航系统中可行驶的区域,提出了一种基于纹理特征的算法,用于分割出城市的非结构化道路中可行的道路区域。首先,为了提取出车道中车辙印对应的纹理特征,通过选取2个频率8个方向的Gabor模板对图像进行变换分析,得到各个像素点的纹理强度以及方向特征,利用其方向特征值对候选消失点进行投票,得票最高点即道路消失点,然后提取出有效投票区域中的直线斜率,建立通过消失点的直线方程来划分出可行的道路区域。实验结果表明,该算法在强光照以及夜间场景下可有效地分割出可行的道路区域,并且不受阴影的影响。

In the visual navigation system,in order to extract the area where the smart cars can travel in,an algorithm based on texture feature was proposed,which could be used to distinguish viable path area from urban unstructured road.First,in order to extract the texture features corresponding to lane ruts,the Gabor templates of two frequencies and eight directions were selected to analyze the transform of the images,so as to achieve the features of the texture intensity and texture directions of the pixels. And the direction features were used to vote the candidate vanishing points,and the point with the most votes was treated as the final vanishing point. The slopes of lines in the valid vote area was extracted,and the linear equations via the vanishing point were established,so as to get the viable path. Experiments show that the proposed algorithm can divide the viable area effectively in the circumstances of strong lights or at nighttime,avoiding the effect of shadows.