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SEM (scanning electron microscope)-based image processing method for carbon nanotube automatic recognition

An image processing, carbon nanotube technology, applied in character and pattern recognition, instruments, computer parts, etc., can solve problems such as long operation cycle, operation level and skill requirements, low magnification, and poor algorithm environment adaptability.

Active Publication Date: 2016-10-26
BEIJING INSTITUTE OF TECHNOLOGYGY
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Problems solved by technology

Therefore, the identification and operation method of nanomaterials such as CNT is particularly important. The operation method of CNT can be divided into two types: non-robot operation and robot operation. The former can quickly and efficiently separate and sort CNT, but the disadvantage is that it is difficult to single Root CNT to operate
The latter can be further divided into teleoperation meth

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  • SEM (scanning electron microscope)-based image processing method for carbon nanotube automatic recognition
  • SEM (scanning electron microscope)-based image processing method for carbon nanotube automatic recognition
  • SEM (scanning electron microscope)-based image processing method for carbon nanotube automatic recognition

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Embodiment Construction

[0024] See attached figure 1 , an image processing method based on SEM for automatic identification of carbon nanotubes on the x-y plane in an extreme environment, which processes object images including: probes (1), CNTs (2), and CNT growth substrates (3).

[0025] The processing flow of the method includes: graying the image; color normalization and binarization; contour gradient calculation; extremum point extraction; and five image processing steps of optimization.

[0026] In the image processing flow of the automatic recognition of the target CNT, the algorithm automatically normalizes the color of the image, in order to cope with the difference in the background brightness of the image caused by the magnification or the change in illumination, the method proposed by the present invention is : Calculate the histogram of the pixel values ​​of the image. According to the characteristics of the image, the partition containing the largest number of pixel values, that is, con...

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Abstract

The present invention provides an SEM (scanning electron microscope)-based image processing method for carbon nanotube automatic recognition. After a scanning electron microscope obtains the images of a probe (1) and CNTs (carbon nanotube) (2), the method includes the following five steps of: image gray processing; color normalization; contour gradient calculation; extreme point extraction; and optimization processing. Thus, one or several target CNTs can be screened out from all recognized CNTs at the edge of a substrate (3), wherein the target CNTs are long, straight, and have few impurities. The image processing method of the invention has the advantages of high robustness, high adaptability to the environment, simple algorithm structure, fast calculation and the like.

Description

technical field [0001] The invention belongs to the technical field of micro-nano operation, and in particular relates to an image processing method for automatic recognition of CNTs (carbon nanotubes) in extreme environments based on SEM. Background technique [0002] Nanomaterials, such as fullerenes, CNTs, graphene, etc., have been widely used in manufacturing, microelectronics, biology, medicine, energy and other fields. Taking CNT as an example, it is used in various nanodevices due to its unique mechanical, electrical and thermal properties. Therefore, the identification and operation method of nanomaterials such as CNT is particularly important. The operation method of CNT can be divided into two types: non-robot operation and robot operation. The former can quickly and efficiently separate and sort CNT, but the disadvantage is that it is difficult to single Operate with root CNT. The latter can be further divided into teleoperation method and automation method. For...

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Application Information

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IPC IPC(8): G06K9/46G06K9/60
CPCG06V10/44G06V10/50G06V10/56G06V10/20G06V2201/122
Inventor 石青王化平郭亚娜孙韬黄强福田敏男
Owner BEIJING INSTITUTE OF TECHNOLOGYGY
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