基于改进霍夫变换与近场滑动窗口的自行车机器人车道视觉识别方法

论文摘要

针对自行车机器人在室外车道循迹过程中容易受到光照变化、阴影干扰、车道线缺失等因素影响的问题，提出一种基于改进霍夫变换与近场滑动窗口的车道视觉识别方法。该方法首先对采集图像进行逆透视变换、边缘检测、中值滤波、ROI裁剪和形态学处理，得到适合车道线提取的二值图像；然后采用改进霍夫变换对车道线进行初步检测并剔除不符合斜率与长度的车道线，结合近场多层滑动窗口对车道边界进行精确校正，并推到是否进入多场景检测拓补车道线；针对单侧或双侧车道线缺失情况，引入多场景状态机进行路径重构；最后通过级联滤波平滑横向偏差输出。实验结果表明，该方法能够提高车道线识别的连续性和稳定性。

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