摘要
传统的光路测试系统在进行道路平整度测量的过程中,在横轴和纵轴的设置都有一定程度的改变,造成道路平整度测量存在误差,从而降低了道路平整度测试的准确性。为此,提出了一种基于亚像素视觉的道路平整度检测方法研究。对路面的边沿进行有效的测量,采用轮廓跟踪的灰度矩亚像素定位方法准确快速的得到路面关键坐标,找到最佳判别位置,得出合理的位置度数据。实验结果表明,这种算法能够有效提高道路平整度测试的准确性,取得了不错的效果。
The traditional optical path test system in the road .roughness measurement process, in the transverse and longitudinal axis Settings have a certain degree of change, causing road roughness measurement error exist, which reduces the road roughness on the accuracy of the test. Therefore, this paper proposes a based on the pixel visual road flatness detection method. The edge occupational effectively measurement, the least square method to get accurate and fast road key coordinates, combined with the Angle error compensation and radial error compensation method, find the best diseriminant position, it is concluded that the reasonable position data. The experimental results show that this algorithm can effectively improve the road roughness on the accuracy of the test, has obtained the good effect.
出处
《科技通报》
北大核心
2013年第10期222-224,共3页
Bulletin of Science and Technology
基金
隧道围岩力学参数反演的自适应神经模糊推理系统(ANFIS)方法研究(KJA201225)
