基于V-视差的障碍物检测改进方法

Improved Method of Obstacle Detection Based on V- disparity

针对传统V-视差方法提取的道路信息与实际道路信息偏离较大,造成障碍物漏检率相对较高的问题,提出一种改进的V-视差障碍物检测方法。在详细分析传统V-视差检测方法的原理和存在的缺陷基础上,提出了极大值约束、较小值抑制约束、距离约束和偏移约束四种条件结合的道路信息提取算法。在采用最小二乘法拟合道路线段后,通过计算道路线段的斜率和截距,并结合视差图检测障碍物。实验结果表明,较传统方法具有较好的障碍物检测效果,且具有一定的实时性和工程实用价值。

The road information extracted by traditional V- disparity method always has relatively large difference to the practical situation which may cause the higher false dismissal probability. An improved method of obstacle detection based on V- disparity is presented. The theory and deficiency of the tradition- al method is analyzed. Firstly the road information extraction algorithm was presented by combining maxi- mum constraint, MIN restrain constraint, distance constraint and excursion constraint, the road segment information was fitted with the least square method, and then the slope and intercept was calculated, final- ly the obstacles were detected by combining the disparity map. The experimental results show that the method has a better detection effect than the traditional methods and it has some real time and practical value in engineering.