结合斜率差和动态融合的自适应轮廓分段

赵辉; 丰懿阳; 尹小恰; 陶卫

doi:10.3788/OPE.20182603.0680

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结合斜率差和动态融合的自适应轮廓分段

信息科学 | 更新时间：2020-07-05

- 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
- 光学精密工程 2018年26卷第3期页码：680-688
- 作者机构：
  
  上海交通大学仪器科学与工程学系, 上海 200240
- 作者简介：
  
  [ "赵辉(1965-), 男, 辽宁阜新人, 博士, 教授, 博士生导师, 分别于1986年、1989年、1994年于哈尔滨工业大学获得学士、硕士、博士学位。主要从事现代传感器、机器视觉、光电检测技术等方面的研究。E-mail:huizhao@sjtu.edu.cn" ]
  [ "丰懿阳(1994-), 男, 江西丰城人, 硕士研究生, 2015年于浙江大学电子信息技术及仪器专业获得学士学位, 主要从事光电传感器和图像处理等方面的研究。E-mail:fengyiyang613@163.com" ]
  [ "尹小恰(1989-), 女, 河南郑州人, 博士研究生, 2011年于河南大学获得学士学位, 2013年于哈尔滨工业大学获得硕士学位, 主要从事机器视觉及图像处理方面的工作。E-mail:xiaoq1216@sjtu.edu.cn" ]
- 基金信息：
  
  上海市闵行区科委资助项目(2014MH116)
- DOI：10.3788/OPE.20182603.0680
  中图分类号： TP391.4;TH692.9
- 收稿日期：2017-10-31，
  
  录用日期：2017-12-7，
  
  纸质出版日期：2018-03-25
- 稿件说明：
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赵辉, 丰懿阳, 尹小恰, 等. 结合斜率差和动态融合的自适应轮廓分段[J]. 光学精密工程, 2018,26(3):680-688.

Hui ZHAO, Yi-yang FENG, Xiao-qia YIN, et al. A self-adaptive curve-segment method combining slope difference and dynamic merge[J]. Optics and precision engineering, 2018, 26(3): 680-688.
赵辉, 丰懿阳, 尹小恰, 等. 结合斜率差和动态融合的自适应轮廓分段[J]. 光学精密工程, 2018,26(3):680-688. DOI： 10.3788/OPE.20182603.0680.

Hui ZHAO, Yi-yang FENG, Xiao-qia YIN, et al. A self-adaptive curve-segment method combining slope difference and dynamic merge[J]. Optics and precision engineering, 2018, 26(3): 680-688. DOI： 10.3788/OPE.20182603.0680.

摘要

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。

Abstract

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.

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references

王宁, 段振云, 赵文辉, 等.视觉检测中齿轮外轮廓分段方法研究[J].组合机床与自动化加工技术, 2016(4):117-120.

WANG N, DUAN ZH Y, ZHAO W H, et al .. Research on method of gear outer contour segmentation in vision measurement[J]. Modular Machine Tool & Automatic Manufacturing Technique, 2016(4):117-120. (in Chinese).

ROSENFELD A, JOHNSTON E. Angle detection on digital curves[J]. IEEE Transactions on Computers, 1973, 22(9):875-878.

NGO P, NASSER H, DEBLED-RENNESSON I, et al . . Adaptive tangential cover for noisy digital contours[C]. Proceedings of the 19th IAPR International Conference on Discrete Geometry for Computer Imagery, Springer, 2016: 439-451.

HORNG J H. An adaptive smoothing approach for fitting digital planar curves with line segments and circular arcs[J]. Pattern Recognition Letters, 2003, 24(1-3):565-577.

HORNG J H, LI J T. A dynamic programming approach for fitting digital planar curves with line segments and circular arcs[J]. Pattern Recognition Letters, 2001, 22(2):183-197.

SARKAR B, SINGH L K, SARKAR D. Approximation of digital curves with line segments and circular arcs using genetic algorithms[J]. Pattern Recognition Letters, 2003, 24(15):2585-2595.

王露, 邢宗义, 陈双, 等.基于自动提取分段点的车轮外形轮廓拟合方法[J].广西大学学报(自然科学版), 2017, 42(2):618-626.

WANG L, XING Z Y, CHEN SH, et al .. A wheel profile fitting method based on automatically extracting subsection points[J]. Journal of Guangxi University (Natural Science Edition), 2017, 42(2):618-626. (in Chinese)

张冉, 张旭, 章海波.截面数据精确分段方法研究[J].轻工机械, 2014, 32(6):70-73, 77.

ZHANG R, ZHANG X, ZHANG H B. Research on accurate segmentation method of sectional data[J]. Light Industry Machinery, 2014, 32(6):70-73, 77. (in Chinese)

RATTARANGSI A, CHIN R T. Scale-based detection of corners of planar curves[C]. Proceedings of the 10th International Conference on Pattern Recognition, IEEE, 1990: 923-930.

乔宇, 黄席樾, 柴毅, 等.基于自适应直线拟合的角点检测[J].重庆大学学报, 2003, 26(2):29-31.

QIAO Y, HUANG X Y, CHAI Y, et al .. Corner point detection based on adaptive line approximation[J]. Journal of Chongqing University, 2003, 26(2):29-31. (in Chinese)

SAINT-MARC P, CHEN J S, MEDIONI G. Adaptive smoothing: a general tool for early vision[C]. Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition, IEEE, 1989: 618-624.

YIN X Q, TAO W, FENG Y Y, et al .. Laser stripe extraction method in industrial environments utilizing self-adaptive convolution technique[J]. Applied Optics, 2017, 56(10):2653-2660.

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