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基于Hough变换的太阳子午线提取方法 被引量:13

Solar Meridian Extraction Method Based on Hough Transformation
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摘要 针对测试环境下偏振光分布模式复杂,特征点发散造成最小二乘法拟合太阳子午线时精度降低的问题,提出了一种基于Hough变换的太阳子午线提取方法。搭建了偏振光分布模式测试系统,利用Stokes矢量原理得到偏振光方位角分布模式,通过设置特征阈值获取太阳子午线特征区域。使用Canny算子检测特征区域边缘,运用Hough变换检测边缘直线方向,结合对称性分布关系获取太阳子午线方位角。通过测试实验,对比分析了所提方法与最小二乘法的测量精确度。实验结果表明,在特征阈值为3<N≤6时,所提方法的测量精确度高于最小二乘法,测量正确度提升了5.53%~87.84%,测量精密度提升了1.81%~92.68%。 Regarding the problem that the distribution pattern of polarized light is complex in test environments and the divergence of feature points reduces the accuracy of fitting solar meridian using the least square method,we propose a solar meridian extraction method based on Hough transformation.First,we build a polarized light distribution pattern test system and obtain the polarization azimuth distribution model based on the Stokes vector principle.By setting the feature threshold,we obtain the feature area of the solar meridian.Then,we detect the feature area edge and direction of the edge lines using the Canny operator and Hough transformation,respectively.Next,we calculate the solar meridian azimuth by combining the symmetry distribution relationship.Through the test experiment,we compare the measurement accuracy of the proposed method with that of the least square method.The experimental results show that the proposed method has higher measurement accuracy than the least square method.When the feature threshold is 3<N≤6,the measurement correctness and measurement precision of the proposed method improved by 5.53%-87.84%and 1.81%-92.68%,respectively,compared with the least square method.
作者 崔岩 周鑫昌 刘亚飞 刘康 褚金奎 Cui Yan;Zhou Xinchang;Liu Yafei;Liu Kang;Chu Jinkui(Key Laboratory for Precision and Non-Traditional Machining Technology,Ministry of Education,Dalian University of Technology,Dalian,Liaoning 116024,China)
出处 《光学学报》 EI CAS CSCD 北大核心 2020年第17期8-14,共7页 Acta Optica Sinica
基金 国家自然科学基金(51675076)。
关键词 大气光学 航向角 太阳子午线 HOUGH变换 最小二乘法 atmospheric optics heading angle solar meridian Hough transformation least square method
作者简介 崔岩,E-mail:yanc@dlut.edu.cn。
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