摘要
针对光照致使光斑图像退化无法准确检测光斑中心的不足,提出了一种自适应ROI提取算法对光斑中心进行准确测量。首先对光斑图像进行结构相似度(SSIM)计算得到自适应ROI,然后将提取到的ROI进行类间方差最大化(Otsu)的图像分割得到光斑二值图,其次对光斑二值图进行圆拟合,最后得到光斑中心坐标。实验结果表明,在平均像素强度低于240时,该算法能较好适应光照影响且计算误差均在0.05%以内,具有较高的精度,能够适用于实际工况下微小位移的测量。
Aiming at the deficiency that the spot image is degraded and the spot center cannot be accurately detected,an adaptive ROI extraction algorithm is proposed to accurately measure the spot center.Firstly the structural similarity(SSIM)calculation is performed on the spot image to obtain an adaptive ROI,and then the extracted ROI is segmented by Otsu to obtain a binary image of the spot,and the second is the Round fitting detection,and finally get the spot center coordinates.The experimental results show that when the average pixel intensity is less than 240,the algorithm in this paper can adapt to the influence of light and the calculation error is within 0.05%.It has high accuracy and can be applied to the measurement of small displacements under actual working conditions.
作者
许丹丹
马增强
钱荣威
周涵
李俊峰
XU Dan-dan;MA Zeng-qiang;QIAN Rong-wei;ZHOU Han;LI Jun-feng(School of Electrical and Electronic Engineering,Shijiazhuang Tiedao University,Shijiazhuang 050043,China;State Key Laboratory of Mechanical Behavior and System Safety of Traffic Engineering Structures,Shijiazhuang Tiedao University,Shijiazhuang 050043,China;不详)
出处
《组合机床与自动化加工技术》
北大核心
2021年第3期83-86,共4页
Modular Machine Tool & Automatic Manufacturing Technique
基金
国家自然科学基金项目(12072207)
全国大学生创新创业项目(201912668009、201910107019)
广东省教育厅特色创新项目(2019KTSCX240)
广东省创新创业训练项目(S202012668014)。
关键词
自适应ROI
结构相似度
图像分割
圆拟合算法
adaptive ROI
structural similarity
image segmentation
round fitting algorithm