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| 基于机器视觉的高精度微纳光纤直径实时测量 |
| High-precision and real-time measurement of micro-nano fiber diameter based on machine vision |
| 投稿时间:2021-03-24 |
| DOI:10.3969/j.issn.1005-5630.2022.01.001 |
| 中文关键词: 微纳光纤 直径测量 机器视觉 图像分割 边缘检测 |
| 英文关键词:micro-nano fiber diameter measurement machine vision image segmentation edge detection |
| 基金项目: |
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| 中文摘要: |
| 针对传统微纳光纤直径测量方法操作复杂、重复性差且易于损伤光纤等问题,开发了一套基于机器视觉的微纳光纤直径测量系统。首先,对系统采集的图像进行预处理和二值化分割,其次,通过Canny边缘算子实现微纳光纤边缘初定位,最后,基于改进Zernike矩的亚像素检测方法精确定位了亚像素级边缘。此外还提出了结合Hough变换与最小二乘法的算法拟合亚像素级边缘点的方案,将系统微纳光纤直径测量精度提升至纳米级。实验测量结果表明,该系统可实现3.51%以内误差的自动化测量,运行时间为2.671 s,更适用于微纳光纤尺寸的高精度实时测量。 |
| 英文摘要: |
| To solve the problems of complex operations, poor repeatability, and contact damage in traditional micro-nano fiber diameter measurement methods, a new measurement system based on machine vision was developed. Firstly, the image was preprocessed and binary segmented in the system, and then the edge of micro-nano fiber was initially located by the Canny edge operator. After that, a sub-pixel detection method based on improved Zernike moment was used to accurately locate the sub-pixel edge. Besides, our system also proposed an algorithm combining Hough transform and the least square method to fit sub-pixel edge points, which improved the measurement accuracy of micro-nano fiber diameters to the nanometer level. The measurement results of micro-nano fiber diameter show that the system can achieve high automation with a measurement error of less than 3.51%, and the running time is 2.671 s. It can be applied to the high-precision and real-time measurement of micro-nano fiber morphology. |
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