复杂背景下连续帧的车轮廓形光条提取方法

Method for extracting light stripes of wheel profiles from consecutive frames in complex background

针对车轮廓形检测中由于不同光照造成的复杂背景,利用光条细且长的形状特征及光条本身颜色特征,对采集图像R分量的二值图像进行外接矩形检测,通过设置矩形区域的筛选条件,实现光条区域在复杂背景下的快速分割,算法中无须过多的阈值参数输入,自适应强,具有较高的可靠性。同时利用图像帧与帧之间的相似性,提出连续帧的边缘扩张算法以进行光条的分割,该算法体现了对物体表面纹理变化的鲁棒性,在保证稳定性的同时,图像检测速度比单帧处理提高了16倍多,平均处理时间为0.22 s,满足轮对廓形检测实时性的需求。

This paper proposed a method that involves detecting the enclosing rectangle of binary images in the R component of ac-quired images,utilizing the shape characteristics of thin and long light stripes and their distinct color characteristics,against complex backgrounds caused by varying illumination conditions in wheel profile detection.By setting filter conditions for rectangular areas,light stripe zones were quickly segmented within complex backgrounds,eliminating the need to repeatedly input threshold parameters,thus en-hancing the algorithm’s adaptability and reliability.Additionally,an algorithm of edge expansion in consecutive frames utilized the simi-larity between image frames to segment light stripes,contributing to the algorithm’s robustness against texture changes on object sur-face.While maintaining stability,the proposed method achieved an image detection speed 16 times higher than that of single-frame pro-cessing methods,meeting the real-time requirements for wheelset profile detection,with an average processing time per frame of 0.22 s.