An Automatic Nanometre Particle Size Detection Algorithm for Scanning Electron Microscopy
WANG Zhi1,2,LI Qi1,HUANG Lu1,GAO Si-tian1,SUN Miao1,2,DONG Ming-li2
1. National Institute of Metrology, Beijing 100029, China
2.Instrument Science and Optoelectronic Engineering College, Beijing Information Science and Technology University, Beijing 100192, China
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.
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2020, Vol. 41 
