大尺寸圆形零部件尺寸高精度视觉测量方法
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1.江苏理工学院;2.常州祥明智能动力股份有限公司

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TP391;TN302

基金项目:

国家自然科学基金(51905235)、江苏省自然科学基金(BK20191037)


High-precision visual measurement method for large-size circular parts
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    摘要:

    圆环类零部件,在进行环形光源和条形光源照射方式下的圆环直径尺寸测量时,通常存在零部件倒角特征成像出现宽边缘、受厚度影响导致圆环边界呈现阴影、表面纹理及擦痕影响图像处理效率、相机视野不足无法单次采集大尺寸圆形零部件高分辨率全景图像等问题。本文提出一种基于改进SURF图像拼接的圆形零部件尺寸测量方法,通过光照优化、图像拼接和亚像素边缘检测实现零部件尺寸的高精度测量。首先,分别提出条形光源45°布置、环形光源垂直向下和条形光源45°组合布置的照射方式,用以消除在零部件成像中存在的宽边缘、阴影、纹理及擦痕等对尺寸测量的影响。其次,改进SURF特征匹配法,定位拼接图像重叠区域进行特征点粗匹配。接着,提出RANSAC算法对特征点进行精匹配,改进图像配准法,等尺寸扩充零部件拼接图像,补充缺失背景区域。然后,提出加权平均融合算法对拼接图像进行平滑处理,获取高分辨率零部件全景图像。最后,改进最小二乘法拟合圆方法,以实现图像中边缘圆环的拟合,通过像素尺寸转化获取零部件实际尺寸值。实验结果表明,该方法相比传统视觉测量方法精度更高,与三坐标测量仪测量参考值相对误差在0.0444%以内。

    Abstract:

    When measuring the diameter of circular parts under the illumination methods of ring light source and strip light source, the problems are usually produced, such as the chamfer features of parts are prone to wide edges in the images, the shadows on the boundaries of circles are appeared due to the influence of thickness, the efficiency of image processing is affected by the surface textures and scratches, and the high-resolution panoramic image of large-sized circular parts is acquired multiple times due to insufficient camera field of view. In this paper, a measurement method for large-size circular parts size based on improved SURF image stitching is proposed, and the high-precision measurement of parts size is realized by illumination optimization, image stitching and sub-pixel edge detection. Firstly, the illumination methods of the strip light source arranged at 45°, the combination of ring light source arranged vertically downward and strip light source arranged at 45° are proposed respectively, thus, the wide edges, shadows, textures and scratches in the images of parts are eliminated, which influence the measurement of parts size. Secondly, the SURF feature matching method is improved to locate overlapping regions of stitching images for coarse matching of feature points. Thirdly, the RANSAC algorithm is proposed for accurate matching of feature points, the image registration method is improved to expand the stitching images of parts to the same size and complement the missing background areas. Fourthly, the weighted average fusion algorithm is proposed to smooth the stitched image, and the high-resolution parts panoramic image is obtained. Finally, the least squares fitting of circles is improved to fit the edge circle in the image, and the actual diameter measurement value of circular parts is obtained through pixel size conversion. The experimental results show that the proposed method is more accurate than the traditional visual measurement method, and the relative error with the CMM measurement reference value is less than 0.0444%.

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  • 收稿日期:2024-04-27
  • 最后修改日期:2024-07-09
  • 录用日期:2024-07-10
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