结合斜率差和动态融合的自适应轮廓分段

A self-adaptive curve-segment method combining slope difference and dynamic merge

为了使用圆弧和直线重建数字轮廓曲线,提出了一种融合了基于斜率差判断断点方法和区段动态融合的数字轮廓曲线自适应分段的方法。首先,利用直线拟合计算轮廓曲线上每点的前后方向的斜率差,求取斜率差的过程使用了自适应长度拟合窗口来平衡精度和速度的关系。然后,将自适应平滑方法应用在方向斜率差曲线上。基于平滑后的斜率差曲线,提取其中间断点作为待选区段分段点。最后,使用基于可视化误差判定的区段动态融合,来从待选分段点中选出一个可视化误差最小的分段方案作为最后的分段结果。仿真测试的结果显示这种分段方法的断点定位误差小于1%。以轴承油沟轮廓为实际测试用例的实验结果证实了这种自适应轮廓分段方法在实际应用中的可行性。

In order to reconstruct the digital contour curve with arc and straight line,a method was proposed to integrate the segmentation of digital contour curve based on the slope difference judgement method and the dynamic segment merge method.First,the slope difference between the front and back directions of each point on the contour curve was calculated using straight line fitting.The process of obtaining the slope difference used the adaptive length fitting window to balance the relationship between the precision and the velocity.Then the adaptive smoothing method was applied to the direction slope difference curve.Based on the smooth slope of the slope curve,the intermittent point was extracted as the selected section segmentation point.Finally,a dynamic merge algorithm based on the perceptual error was used to select a segmentation scheme with the smallest perceptual error from the selected segments as the final result.The simulation results show that the error of this segmentation method is less than 1%.The experimental results of the contours of bearing oil groove as the actual test cases show the feasibility of this adaptive contour segmentation method in practical application.