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AFM image processing for estimating the number and volume of nanoparticles on a rough surface
Author(s) -
Liu Qinghua,
Wang Huiliang,
Liu Jun,
Huang Haiyang
Publication year - 2011
Publication title -
surface and interface analysis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.52
H-Index - 90
eISSN - 1096-9918
pISSN - 0142-2421
DOI - 10.1002/sia.3722
Subject(s) - nanoparticle , surface (topology) , volume (thermodynamics) , smoothing , materials science , segmentation , filter (signal processing) , rough surface , polymer , image processing , nanotechnology , computer science , artificial intelligence , computer vision , composite material , image (mathematics) , mathematics , geometry , physics , thermodynamics
This article presents the method of computer automatic recognition and measurement of the number and volume of nanoparticles formed on a rough surface by smoothing, enhancement and segmentation of image processing. The grafted grains (nanoparticles) on polyethylene surface are taken as the example. This method uses shock filter enhancement and globally convex segmentation to separate the nanoparticles from the polymer substrate surface. Then the nanoparticles are extracted from the rough surface, and the number and volume of nanoparticles on the rough surface are determined. By applying this method to analyze the surfaces irradiated for different time, the number and volume of grafted grains are obtained and they are consistent with the results obtained manually. Copyright © 2010 John Wiley & Sons, Ltd.