基于机器视觉的光纤几何参数检测算法设计
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摘要
为了满足工业检测中快速检测光纤横截面几何参数的需求,运用数字图像处理技术实现光纤几何参数测量。最大类间方差法用于分割高对比度光纤二次涂覆层区域;改进Canny算法用于提取低对比度光纤一次涂覆层和包层边缘,该算法在传统Canny算法的基础上运用局部区域距离阈值法代替双阈值法中的高阈值,实现单一边缘响应原则;结合使用二次曲线标准化法和齐次方程法用于边缘曲线拟合,并用高斯-牛顿迭代法求解光纤几何参数。检测结果与高精度光纤测试仪FGM-502进行对比,结果证明本文研究的光纤检测算法的有效性及准确性,满足企业光纤几何参数检测需求。
To meet the requirements of rapid detection of fiber cross-section geometry parameters in the measurement of industry, digital image processing technology is used to realize fiber geometric parameter measurement. The high-contrast fiber secondary coating layer region is segmented based on Otsu method; the edge detection is performed on the low-contrast fiber primary coating layer and cladding layer based on the improved Canny algorithm. The algorithm uses the local region distance threshold based on the traditional Canny algorithm. The method replaces the high threshold in the double threshold method to realize the single edge response principle; the curve is fitted to the edge based on the combination of the quadratic curve normalization method and the homogeneous equation method, and the Gauss-Newton iteration method is used to solve the fiber geometric parameters. The test results are compared with the high-precision fiber tester FGM-502, the results prove the validity and accuracy of the fiber detection algorithm studied in this paper, and the accuracy meets the requirements of enterprise fiber geometry parameter detection.
To meet the requirements of rapid detection of fiber cross-section geometry parameters in the measurement of industry, digital image processing technology is used to realize fiber geometric parameter measurement. The high-contrast fiber secondary coating layer region is segmented based on Otsu method; the edge detection is performed on the low-contrast fiber primary coating layer and cladding layer based on the improved Canny algorithm. The algorithm uses the local region distance threshold based on the traditional Canny algorithm. The method replaces the high threshold in the double threshold method to realize the single edge response principle; the curve is fitted to the edge based on the combination of the quadratic curve normalization method and the homogeneous equation method, and the Gauss-Newton iteration method is used to solve the fiber geometric parameters. The test results are compared with the high-precision fiber tester FGM-502, the results prove the validity and accuracy of the fiber detection algorithm studied in this paper, and the accuracy meets the requirements of enterprise fiber geometry parameter detection.
引文
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[13] 刘庆民,张蕾,吴立群,等.基于机器视觉的非均匀分布点圆度误差评定[J].计量学报,2016,37(6):567-570.
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[15] 庞鸿锋,潘孟春,王伟,等.基于高斯牛顿迭代算法的三轴磁强计校正[J].仪器仪表学报,2013,34(7):67-72.
[2] 郝爱华,毛智礼,贺锋涛.单模及多模光纤折射率分布测量方法研究[J].应用光学,2005,26(5):41-44.
[3] 高迎春.基于折射近场法测量光纤折射率分布的仿真研究[D].哈尔滨:哈尔滨工程大学,2012.
[4] SAYERS A E, DORSEY W M, O"HAVER K W, et al. Planar near-field measurement of digital phased arrays using near-field scan plane reconstruction[J]. IEEE Transactions on Antennas and Propagation, 2012,60(6):2711-2718.
[5] 韦哲,刘昌锦.相控阵天线方向图的近场功率测量法研究[J].测控技术,2014,33(8):30-32,36.
[6] EL-DIN M A S, WAHBA H H. Investigation of refractive index profile and mode field distribution of optical fibers using digital holographic phase shifting interferometric method[J]. Optics Communications, 2011,284(16-17):3846-3854.
[7] 闫成,黄素娟,曾俊璋,等.基于数字全息的双包层光纤参数测量[J].光电子·激光,2016,27(5):519-527.
[8] 何志勇,孙立宁,黄伟国,等.基于Otsu准则和直线截距直方图的阈值分割[J].光学精密工程,2012,20(10):2315-2323.
[9] 吴凤和.基于计算机视觉测量技术的图像轮廓提取方法研究[J].计量学报,2007,28(1):18-22.
[10] TRUJILLO-PINO A,KRISSIAN K,ALEMAN-FLORES M,et al. Accurate subpixel edge location based on partial area effect [J]. Image and Vision Computing,2013,31(1):72-90.
[11] WU Y, ZHAO X P, JIN Y, et al. Extracting golden area from image based on canny operator[J]. Applied Mechanics and Materials,2015,731(6):201-204.
[12] 郭成成,郑守住.一种有效的影像中椭圆形目标提取方法[J].电子测量技术,2017,40(4):167-171.
[13] 刘庆民,张蕾,吴立群,等.基于机器视觉的非均匀分布点圆度误差评定[J].计量学报,2016,37(6):567-570.
[14] 黄斌,孙永荣,杨博文,等.迭代最小二乘椭圆拟合的锥套图像检测与跟踪[J].中国图象图形学报,2014,19(8):1202-1209.
[15] 庞鸿锋,潘孟春,王伟,等.基于高斯牛顿迭代算法的三轴磁强计校正[J].仪器仪表学报,2013,34(7):67-72.