应用光学, 2020, 41 (2): 302, 网络出版: 2020-04-23  

基于干涉条纹骨架的毛刺去除算法 下载: 631次

Burr removal algorithm based on interference fringe skeleton
作者单位
福建师范大学 医学光电科学与技术教育部重点实验室 福建省光子技术重点实验室,福建 福州 350007
摘要
精确去除骨架毛刺是干涉条纹骨架提取的最为关键的一个环节,可以应用于激光的干涉条纹检测。提出一种基于骨架特征的去除干涉条纹骨架毛刺算法,算法的主要方案包括:获取骨架的特征点、八邻域链表追踪。首先对像素点进行逐个扫描,获取骨架的4种特征点:端点、节点、毛刺点、主干点,其次使用基于特征点的八邻域链表算法提取所有毛刺点、主干点,然后基于节点进行差分运算并剔除毛刺,最后对处理后的图像进行迭代处理直到干涉条纹骨架毛刺完全去除。利用OpenCV机器视觉算法对毛刺图像去除进行仿真,得到的结果通过1 000个毛刺图片验证,毛刺去除的正确率达到94%。该算法相较于传统方案具有较高的针对性,保留骨架主干部分,去除其余毛刺部分,在干涉条纹检测方面具有广阔的应用前景。
Abstract
Accurate removal of the skeletal burrs is the most critical step in the extraction of interference fringe skeleton, which can be applied in laser interference fringe detection. A burrs removal algorithm of interference fringe skeleton based on skeleton features is proposed,which includes the acquisition of feature points of skeleton and the tracking of the eight-neighborhood linked list. First, the pixel points are scanned one by one to obtain the four feature points of the skeleton: endpoints, nodes, glitch points, and backbone points. Then, the algorithm of eight neighborhood linked list based on feature points is used to extract all the glitch points and backbone points, and the difference operation was performed based on nodes to remove the burrs. Finally, the processed image is iterated until the interference fringe skeleton burrs are completely removed. The OpenCV machine vision algorithm was used to simulate the burrs image removal, the results were verified by 1 000 pieces of burrs images, and the correct rate of burrs removal is 94%. Compared with the traditional scheme, the proposed algorithm has a higher pertinence, retains the backbone of the skeleton, and removes the remaining burrs, which has a broad application prospect in interference fringe detection.

梅启升, 王敏, 梁秀玲. 基于干涉条纹骨架的毛刺去除算法[J]. 应用光学, 2020, 41(2): 302. Qisheng MEI, Min WANG, Xiuling LIANG. Burr removal algorithm based on interference fringe skeleton[J]. Journal of Applied Optics, 2020, 41(2): 302.

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