基于线结构光的反射金属表面条纹中心提取方法

Limei Song, Jinsheng He, and Yunpeng Li
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摘要

使用线结构光测量金属表面形貌时,由于金属表面的光学特性和散射噪声的影响,条纹中心的提取误差很大。本文针对这一问题,提出了一种基于自适应阈值分割和梯度加权策略的亚像素条纹中心提取方法。首先,我们分析了被测金属表面形态的条纹图像特征。根据图像的形态特征,对图像进行分割,以消除背景噪声的影响,并获得图像中的感兴趣区域。然后,我们使用灰重力法得到条纹的粗略中心坐标。我们以粗略中心坐标为参考,在宽度方向上扩展条纹,确定条纹的中心,以便在分割后进行提取。接下来,我们利用区域的灰度自适应地确定边界阈值。最后,我们使用梯度加权策略提取亚像素条纹中心。实验结果表明,所提出的方法能有效消除金属表面散射对三维重建的干扰。测量标准块的平均高度误差为 0.025 毫米,测量精度的重复性为 0.026 毫米。
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Center extraction method for reflected metallic surface fringes based on line structured light
Using line structured light to measure metal surface topography, the extraction error of the stripe center is significant due to the influence of the optical characteristics of the metal surface and the scattering noise. This paper proposes a sub-pixel stripe center extraction method based on adaptive threshold segmentation and a gradient weighting strategy to address this issue. First, we analyze the characteristics of the stripe image of the measured metal’s surface morphology. Relying on the morphological features of the image, the image is segmented to remove the effect of background noise and to obtain the region of interest in the image. Then, we use the gray-gravity method to get the rough center coordinates of the stripes. We extend the stripes in the width direction using the rough center coordinates as a reference to determine the center of the stripes for extraction after segmentation. Next, we adaptively determine the boundary threshold utilizing the region’s grayscale. Finally, we use the gradient weighting strategy to extract the sub-pixel stripe center. The experimental results show that the proposed method effectively eliminates the interference of metal surface scattering on 3D reconstruction. The average height error of the measured standard block is 0.025 mm, and the repeatability of the measurement accuracy is 0.026 mm.
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