An automatic algorithm for determination of the nanoparticles from TEM images using circular hough transform
•Automated measurement of the number and the average primary diameter of the nano particles from TEM images.•This method is based on the modified version of the hough transform with pre-processing modifications on TEM images.•The method has been tested on several TEM images with different complexity...
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| Published in | Micron (Oxford, England : 1993) Vol. 96; pp. 86 - 95 |
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| Main Authors | , |
| Format | Journal Article |
| Language | English |
| Published |
England
Elsevier Ltd
01.05.2017
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| Subjects | |
| Online Access | Get full text |
| ISSN | 0968-4328 1878-4291 1878-4291 |
| DOI | 10.1016/j.micron.2017.02.008 |
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| Summary: | •Automated measurement of the number and the average primary diameter of the nano particles from TEM images.•This method is based on the modified version of the hough transform with pre-processing modifications on TEM images.•The method has been tested on several TEM images with different complexity in the images.•It has less than 5% difference over 11 different TEM images, relative to manual sizing.
Nanoparticles have a wide range of applications in science and technology, and the size distribution of nanoparticles is one of the most important statistical properties. Transmission electron microscopy (TEM) or X-ray diffraction is commonly used for the characterization and measuring particle size distributions, but manual analysis of the micrographs is extremely labor-intensive. Here, we have developed an image processing algorithm for measuring particle size distributions from TEM images in the presence of overlapped particles and uneven background. The approach is based on the modified circular Hough transform, and pre and post processing techniques on TEM image to improve the accuracy and increase the detection rate of the nano particles. Its application is presented through several images with different noises, uneven backgrounds and over lapped particles. The merits of this robust quantifying method are demonstrated by comparing the results with the data obtained through manual measurement. The algorithm allows particles to be detected and characterized with high accuracy. |
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| Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
| ISSN: | 0968-4328 1878-4291 1878-4291 |
| DOI: | 10.1016/j.micron.2017.02.008 |