基于机器视觉滑轨截面圆弧尺寸的测量方法

Measurement method of arc dimension of slide section based on machine vision

  • 摘要: 为解决汽车座椅滑轨截面圆弧尺寸人工检测效率低、一致性差的问题,文章提出了一种基于卡尺边缘检测与Tukey算法相结合的测量方法,实现滑轨截面圆弧尺寸高效率、高精度的检测。首先对采集到的图像做双边滤波处理,去除图像中的噪声,再通过HALCON算法库中的Emphasize算子对图像做处理,突出图像边缘信息;然后通过卡尺边缘检测算法提取圆弧边缘点;最后结合加权Tukey的最小二乘法分离出异常点并完成圆的拟合。实验结果表明,该方法可实现滑轨截面圆弧尺寸的快速检测,测量系统稳定性好、可靠性高,测量误差均在0.08 mm之内,重复测量精度可达0.02 mm。

     

    Abstract: In order to solve the problems of low efficiency and poor consistency in manual detection of the arc dimension of the slide section of car seat, a measuring method based on the combination of caliper edge detection and Tukey algorithm was proposed, which realized the detection of the arc dimension of the slide section with high efficiency and high precision. First, the collected images were processed by bilateral filtering to remove the noise in the images, and a emphasize operator in the HALCON algorithm library was used to process the images and highlight the edge information of the images. Then the arc edge points were extracted by caliper edge detection algorithm. Finally, the outliers were separated by the least square method of weighted Tukey and the circle fitting was completed. The experimental results showed that this method could realize the rapid detection of the arc dimension of the slide section, and the measuring system had a good stability and high reliability. The measuring errors were all within 0.08 mm, and the repeated measurement accuracy could reach 0.02 mm.

     

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