改进的光照不变道路检测算法

Improved Road Detection Algorithm Based on Illuminant Invariant

针对大多数道路检测方法存在光照变化敏感,阴影导致误检、漏检等问题,提出了一种改进的光照不变道路检测算法.首先将道路图像RGB空间转换为几何均值对数色度空间;然后根据Shannon熵确定相机轴标定角θ,利用Chebyshev理论去除θ奇异值,得到光照无关图Iθ;其次通过随机抽样方法提取道路样本点,包括道路基准样本点和道路参考样本点;最后建立道路置信区间分类器,将道路从背景中分离出来.实验结果表明,该算法能很好地消除光照变化和阴影对道路检测的影响,检测精度高,能满足实际道路检测实时性要求.

Aiming at the problems that most road detection methods are sensitive to variation of illumination and shadow, which lead to false detection or leak detection, improved road detection algorithm based on illumination invariant is proposed. First, the thesis transformed RGB space of road images into logchromaticity space by geometric mean. And then, according to Shannon entropy, camera angle θ of axis calibration is determined. Using Chebyshev＇s theory, it removed singular value of θ and got illumination invariant images Iθ. Besides, some sampling points of road are extracted by a random sampling, which include standard sample points and referenced sample points. Finally, a confidence interval classifier of road is established, which could detect road area. The experimental results show that the proposed algorithm not only can effectively eliminate the influence of illuminant variance and shadows on road detection, but also can guarantee high detection precision and real-time requirements.