一种实时鲁棒的非结构化道路检测算法

Real-time and robust method for unstructured roads detection

针对智能导航系统中的非结构化道路检测问题,提出一种分块分段混合高斯模型和B样条曲线模型相结合(block-segment Gaussian mixture and B-spline model,BSGMM_BS)的非结构化道路检测算法。该算法利用待处理图像的彩色信息对道路区域和非道路区域进行混合高斯建模,利用分块分段方法提取道路边界点,最后使用最小二乘法求解B样条曲线最优控制点,完成对道路双边界的拟合。实地测试和对比实验表明,该算法实时性好,对阴影、光照变化等影响具有较强的抗干扰性。

This paper proposed an unstructured road detection algorithm based on block-segment Gaussian mixture model and B-spline curve model,called BSGMM_BS.First modeled the road and off-road regions by Gaussian mixture color model.Then introduced a method called block-segment method to extract the road edge points.Finally fitted two boundaries of the lane by the B-spline curve in which the best control points were searched by the least square method.Field tests and comparison experiments show that the algorithm is real-time and is robust against shadows,illumination variations.