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中文摘要：
城市半结构化道路交通环境中，为提高道路模型对复杂环境的适应性，解决算法难以在效率和鲁棒性间达到平衡的问题，提出基于不定Bezier变形模板的城市道路检测算法。算法对输入图像进行逆透视变换，根据相机参数和车辆状态自适应设置静态和动态两层感兴趣区域，利用透视图中道路标识线平行向前延伸的特点，提出混合高斯方向异性滤波器，对图像进行预处理。引入Bezier样条曲线，构造不定道路变形模板，将道路识别问题转化为模板参数假设检验问题，使用改进RANSAC算法求解模板参数。为提高求解速度，提出层次搜索优化算法，建立期望区域和解集空间，采用粗搜索与精搜索相结合的方法，实现模板参数快速搜索。试验结果表明，该方法在城市道路环境中可以快速准确提取车道线，并对典型道路干扰具有较好免疫作用。
英文摘要：
In order to improve the adaptability of road model for complex environments, achieve a balance between efficiency and robustness in urban semi-structured road envir6nment, a novel road detection algorithm based on uncertain Bezier deformable template is improved. It adaptively sets two-tier region of interest containing static and dynamic area for IMP according to camera parameters and vehicle status and proposed Ganssian mixture directional filter for pretreatment. It constructs uncertain road deformable template using Bezier curve, and convert the road recognition problem to template parameter hypothesis testing problem. A modified RANSAC algorithm is also wsed to solve the uncertain deformable template parameters. In order to improve the speed of solving, a level search optimization algorithm which using a combination of coarse search and fine search method is proposed. The test results show that the method can rapidly and accurately extract the lane and have good immune function for typical roads interference in the urban road environment.
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