电子测量与仪器学报

吴国新,祁垠燕,左云波,董远秋,陈炫宇.法线引导和优化邻域角度划分的线结构光中心提取[J].电子测量与仪器学报,2026,40(3):262-272

法线引导和优化邻域角度划分的线结构光中心提取

Normal-guided optimized angle-based center extraction for line structured light

DOI：

英文关键词:line structured light normal guidance improve the grayscale centroid method extreme value method 3σ criterion eight neighborhood

基金项目:

作者	单位
吴国新	1.北京信息科技大学现代测控技术教育部重点实验室北京100192；2.北京信息科技大学机电工程学院北京100192
祁垠燕	1.北京信息科技大学现代测控技术教育部重点实验室北京100192；2.北京信息科技大学机电工程学院北京100192
左云波	1.北京信息科技大学现代测控技术教育部重点实验室北京100192；2.北京信息科技大学机电工程学院北京100192
董远秋	1.北京信息科技大学现代测控技术教育部重点实验室北京100192；2.北京信息科技大学机电工程学院北京100192
陈炫宇	1.北京信息科技大学现代测控技术教育部重点实验室北京100192；2.北京信息科技大学机电工程学院北京100192

Author	Institution
Wu Guoxin	1.Key Laboratory of Modern Measurement and Control Technology, Ministry of Education, Beijing Information Science and Technology University，Beijing 100192, China; 2.School of Mechanical and Electrical Engineering, Beijing Information Science and Technology University，Beijing 100192, China
Qi Yinyan	1.Key Laboratory of Modern Measurement and Control Technology, Ministry of Education, Beijing Information Science and Technology University，Beijing 100192, China; 2.School of Mechanical and Electrical Engineering, Beijing Information Science and Technology University，Beijing 100192, China
Zuo Yunbo	1.Key Laboratory of Modern Measurement and Control Technology, Ministry of Education, Beijing Information Science and Technology University，Beijing 100192, China; 2.School of Mechanical and Electrical Engineering, Beijing Information Science and Technology University，Beijing 100192, China
Dong Yuanqiu	1.Key Laboratory of Modern Measurement and Control Technology, Ministry of Education, Beijing Information Science and Technology University，Beijing 100192, China; 2.School of Mechanical and Electrical Engineering, Beijing Information Science and Technology University，Beijing 100192, China
Chen Xuanyu	1.Key Laboratory of Modern Measurement and Control Technology, Ministry of Education, Beijing Information Science and Technology University，Beijing 100192, China; 2.School of Mechanical and Electrical Engineering, Beijing Information Science and Technology University，Beijing 100192, China

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全文下载次数: 196

中文摘要:

航空发动机叶片属于发动机核心组件高精密部件之一，保障其型面快速、精确的测量至关重要。激光光条中心线的精确提取是三维测量过程中的关键环节，对测量精度具有直接影响。针对现有光条中心提取方法在光条宽度不均、高曲率及噪声环境下精度和鲁棒性不足的问题，提出一种结合法线引导的极值法与改进的空间灰度重心推进法，优化提取中心精度。该方法首先基于Steger法判断中心线预估位置；随后利用极值法识别潜在重要特征区域，并在法线方向上通过改进的空间灰度重心法进行加权计算，完成光条中心初步提取；再应用改进八邻域区域角度方法筛取有效点，并结合3σ准则过滤异常数据点,最终获得精确中心点坐标。采用对比实验验证，算法在标准测试图像上的中心提取均方根误差为0.058 pixel,有效保留了光条细节；每帧运算时间约为0.755 ms，较Steger算法提升约6倍，较传统灰度法提升约3倍，有效解决了曲率中心倾斜问题。此外，在模糊样本及加入高斯噪声图像的测试中，拟合准确率较Steger法提高了3.7%,噪声鲁棒性RMSE相比传统算法下降了6.9%，显示了算法在复杂环境下的优越性和实用性，为航空航天制造及光学精密仪器的高精度测量工程应用提供有效技术支持。

英文摘要:

Aero-engine blades, as one of the core high-precision components of the engine, require rapid and accurate surface measurement to ensure engine performance. Accurate extraction of laser stripe centerlines is a critical step in three-dimensional measurement, directly affecting measurement accuracy. To address the limitations of existing center extraction methods under uneven stripe width, high curvature, and noisy conditions, this study proposes a centerline extraction algorithm combining normal-guided extremum method with an improved spatial grayscale centroid propagation approach to optimize extraction precision. The method first estimates the centerline position using the Steger method; potential key feature regions are then identified via the extremum method, and weighted spatial grayscale centroid calculation along the normal direction is applied to obtain the initial stripe center. An improved eight-neighborhood angular selection is subsequently used to screen effective points, and outliers are removed using the 3σ criterion, ultimately yielding precise center coordinates. Comparative experiments demonstrate that the algorithm achieves a root mean square error (RMSE) of 0.058 pixel on standard test images, effectively preserving stripe details; 1 frame processing time is approximately 0.755 ms, achieving a 6-fold speed improvement over the Steger method and a 3-fold improvement over the conventional grayscale method, effectively addressing the curvature-induced centerline tilt problem. Furthermore, tests on blurred samples and images with added Gaussian noise show a 3.7% increase in fitting accuracy and a 6.9% decrease in RMSE compared with traditional methods, indicating superior robustness and practical applicability. The proposed algorithm provides effective technical support for high-precision measurement applications in aerospace manufacturing and optical precision instruments.

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