基于消失点和主方向估计的道路分割算法

现有基于消失点估计的道路分割算法要求消失点位于图像内部，并且算法计算复杂度高，难以排除局部纹理特征较强的干扰点.针对这些问题，提出一种基于道路主方向的消失点估计和道路分割算法.首先根据道路主方向的定义对有效投票点进行筛选，然后提出一种多维投票策略，记录待定消失点在各纹理方向的投票信息，并运用该信息判断消失点是否在图像内；最后提出基于道路主方向的边界拟合策略，利用多维投票数据来进行道路边界提取.主观评价和量化分析表明，与经典算法相比，所提算法具有更好的精确度和执行速度，并且当消失点位于图像外部时算法仍有较好的分割效果.

Road Segmentation Based on Vanishing Point and Principal Orientation Estimation

Most existing road segmentation algorithms based on vanishing point estimation demand the vanishing point locats inside the image, and they are always time-consuming and cannot effectively overcome the interference of noise which has strong texture features. This paper focuses on these problems, and proposes a road segmentation method based on principal orientation and vanishing point estimation. Firstly, the valid voters are selected by the restrains of road principal orientation. Then a multi-dimension voting scheme is presented, which records the voting information in different orientations of candidate vanishing point, and these information is later used to judge whether the vanishing point is located inside image. Finally, a boundary fitting strategy based on principal orientation is proposed, which extracts the road region according to the data generated on the multi-dimension voting stage. Quantitative and qualitative experiments show that the proposed road segmentation method is more accurate and faster than the traditional algorithms, and it can still work well when the vanishing point is located outside the image.