基于数学几何学,提出一种扫描电镜纳米颗粒粒径自动检测方法,该方法利用电镜颗粒图像的粒径分布及形状信息,采用长短轴比值和区域面积2种不同参数对颗粒是否团簇或残缺进行判断,实现筛选单个的完整颗粒,并使用MATLAB对不同粒径参数的颗粒宽边缘形状进行提取,运用最小二乘法求出颗粒粒径的像素值,经转化后得到真实值,从而实现了微纳米颗粒粒径的自动检测。试验选取聚苯乙烯纳米颗粒对方法进行验证,结果表明:对于团簇残缺较少的图像,采用长短轴比值和面积2种参数进行筛选均能准确有效提取单点颗粒,但团簇残缺颗粒较多时,采用长短轴比值效果更加准确,且计算颗粒粒径与实际值吻合良好。
Abstract
A new automatic detection method of nano-particle size in scanning electron microscopy (SEM) test is proposed based on mathematical geometry. The method has two different parameters, the ratio of long and short axes and the area of region, which are used to judge whether the particles are clustered or incomplete based on the particle size distribution and shape information in the SEM pictures. And the complete single particles can be get, then use MATLAB to extract the wide edge shape of particles with different size. The pixel value of different particles is obtained by the least square method, and the real value can be calculated with transformation, thus realizing the automatic detection of different particles. The test results of polystyrene nanoparticles were selected to verify the method, which show that the two parameters can accurately and effectively extract single point particles in the case of less incomplete clusters. While the ratio parameter is more accurate if there are more incomplete particles in clusters, and the results of automatic detection are in good agreement with the actual values.
关键词
计量学 /
粒径测量 /
纳米颗粒 /
扫描电子显微镜 /
长短轴比
Key words
metrology /
particle size measurement /
nanometre particle /
SEM /
long and short axis ratio
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基金
国家重点研发计划(2016YFA0200901);自然科学基金青年基金(51805505);中国计量科学研究院基本科研业务费(AKY1817);北京信息科技大学2018—2019年度“实培计划”项目
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