电子测量与仪器学报

曹震,巢渊,徐魏,杜帅帅,张敏.基于改进梯度加权的零件图像高精度聚焦方法[J].电子测量与仪器学报,2023,37(11):132-142

基于改进梯度加权的零件图像高精度聚焦方法

High-precision focusing method for parts image based on improved gradient weighting

DOI：

英文关键词:auto-focus articulation evaluation light source optimization gradient weighting vision measurement

基金项目:国家自然科学基金(51905235)、江苏省自然科学基金(BK20191037)项目资助

作者	单位
曹震	1. 江苏理工学院机械工程学院
巢渊	1. 江苏理工学院机械工程学院，2. 河海大学物联网工程学院，3. 常州祥明智能动力股份有限公司
徐魏	1. 江苏理工学院机械工程学院
杜帅帅	1. 江苏理工学院机械工程学院
张敏	3. 常州祥明智能动力股份有限公司

Author	Institution
Cao Zhen	1. School of Mechanical Engineering, Jiangsu University of Technology
Chao Yuan	1. School of Mechanical Engineering, Jiangsu University of Technology,2. College of Internet of Things Engineering, Hohai University,3. Changzhou Xiangming Intelligent Drive System Corporation
Xu Wei	1. School of Mechanical Engineering, Jiangsu University of Technology
Du Shuaishuai	1. School of Mechanical Engineering, Jiangsu University of Technology
Zhang Min	3. Changzhou Xiangming Intelligent Drive System Corporation

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中文摘要:

以标准量块为实验对象,针对环形光源照射下的零件图像易出现倒角特征成像存在宽边缘,手动调焦缺乏相机聚焦的客观性而导致图像聚焦不精确等问题,提出一种基于改进梯度加权的零件图像高精度聚焦方法。首先采用条形光源 45°布置的照射方式,消除倒角特征在成像中的宽边缘。其次,基于改进 Otsu 实现自适应分割阈值获取,提取图像特征边缘点。接着, 基于 4 方向 Sobel 算子获取边缘点梯度值。然后,根据像素点与其 8 邻域像素点灰度分布差异值大小,获取像素点梯度加权系数。最后,通过改进梯度加权的聚焦评价函数完成图像清晰度评价,获取精确聚焦图像,实现高精度尺寸测量。实验结果表明, 该方法相比传统高精度测量方法精度更高,与人工测量值相对误差在 0. 002 4%以内。改进聚焦评价函数相比传统评价函数清晰度比率平均提升 75 倍,灵敏度因子平均提升 5 倍,陡峭度平均提升 1 倍。

英文摘要:

Taking the standard gauge block as the experimental object, to address the problems that the chamfer features of the parts are prone to wide edges in the parts image under the illumination of ring light source, and the inaccurate image focusing is caused by manual focusing, which lacks the objectivity of camera focusing, etc. , a high-precision focusing method of parts image based on improved gradient weighting is proposed. Firstly, the illumination method of the strip light source arranged at a 45-degree angle is adopted to eliminate the wide edges of the chamfer features in the parts image. Secondly, the feature edge points of image are extracted by the adaptive segmentation threshold based on the improved Otsu. Then, the gradient values of edge pixels are obtained based on the 4- direction Sobel operator. Then, according to the grayscale distribution difference between the pixel and its 8 neighboring pixels, the gradient weighting coefficient of the pixel is obtained. Finally, the sharpness evaluation of image is completed by the improved function of gradient-weighted focus evaluation, thus, the accurate focus image is obtained and the high-precision measurement of size is realized. The experimental results show that the proposed method is more accurate than the traditional high-precision measurement method, and the relative error with the manual measurement is less than 0. 002 4%. The improved focus evaluation function in this paper is improved by 75 times in sharpness ratio, 5 times in sensitivity factor and double in steepness on average compared with the traditional evaluation functions

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