摘要
介绍了一种新的面向智能无人机应用的道路检测与跟踪算法.首先从电子道路地图中得到标示道路初始区域的合成图像,然后利用光学图像的距离变换图像、合成图像的边缘图像等信息把道路检测问题表述为一最优化问题,最后利用迭代算法解此问题得到路面区域.道路跟踪利用前一帧检测结果的预测值初始化其对应的优化问题.实验证明该方法具有较高的稳定性和适应能力.
A novel road detection and tracking algorithm for intelligent pilotless aircraft applications was illustrated. Initially, synthetic image was extracted from electron road maps to initialize the road areas. Then, road detection was expressed as a minimizing problem by means of using distance transformation of input image and edges of synthetic image. Finally an iterative algorithm took shape and was applied to solve the minimizing problem mentioned above to abtain road regions. Road tracking method initialized its corresponding minimizing problem utilizing the prediction image out of the detection results of previous video frames. Concerning the function of this method, strict experimental results are presented to demonstrate the satisfactory performances of our approach with its highly stability and adaptability.
出处
《北京航空航天大学学报》
EI
CAS
CSCD
北大核心
2007年第4期445-449,共5页
Journal of Beijing University of Aeronautics and Astronautics
关键词
道路检测和跟踪
最小化思想
迭代算法
road detection and tracking
minimization philosophy
iterative algorithm