Carbon nanotubes are typical one-dimensional materials that can be metals or semiconductors. At present, research on SEM image processing methods is becoming more and more common, so it is particularly meaningful to use SEM to automatically identify carbon nanotubes. In this paper, a scanning electron microscope-based automatic detection method for carbon nanotubes is proposed, and a method for classifying low-dimensional nanomaterials in scanning electron microscope (SEM) images is also presented. Based on the scanning electron microscope images of nanomaterials, the surface texture of the materials was extracted by the automatic detection technology of carbon nanotubes (CNTs). The test results show that the simulation results of SEM images of 10 different materials show that the classification accuracy of the method can reach 93.75%, which proves its effectiveness in practical engineering.

Feigao Li. Image Processing Method for Automatic Identification of Carbon Nanotubes Based on SEM. International Journal of Big Data Intelligent Technology (2021), Vol. 2, Issue 4: 17-32. https://doi.org/10.38007/IJBDIT.2021.020403.

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