Low-dimensional nano material identification method based on SEM image

Abstract

The invention belongs to the crossed technical field of computer mode identification and nano material, and relates to a low-dimensional nano material identification method based on an SEM image. The method comprises the following steps of: (1) preprocessing a known nano material SEM image sample; (2) performing two-dimensional wavelet transformation on the preprocessed image to get sub-image matrixes on different frequency bands; (3) extracting characteristics of the sub-image matrixes on each frequency band, and taking a statistical value of each sub-image matrix as a characteristic value for representing surface texture of the nano material; (4) according to the characteristic value, taking a Gaussian radial basis function as a support vector machine kernel function to find an optimal hyperplane between any two classes, and creating a classification model for different classes of nano materials; (5) extracting a texture characteristic value of the known nano material SEM image sample, and identifying the unknown nano material by voting according to the classification model obtained in the step (4). The low-dimensional nano material identification method based on the SEM image represents and distinguishes different nano material structure types more accurately and effectively, and has the advantages of high accuracy, strong expansibility, high degree of automation and the like.

Description

technical field [0001] The invention belongs to the intersecting field of computer pattern recognition and nanometer materials, and relates to a method for realizing low-dimensional nanometer material recognition based on computer image processing, which can be used for shape characterization of nanomaterials, and provides guidance for synthesis and production of nanomaterials. Background technique [0002] At present, low-dimensional nanotechnology (usually including one-dimensional and two-dimensional nanotechnology), especially one-dimensional nanotechnology has gradually become a revolutionary force in industrial production and scientific research, and represents the future development direction of nanotechnology to a certain extent; however, due to The structure and shape of low-dimensional nanomaterials are complex and diverse, and the corresponding auxiliary detection methods and morphology characterization technologies are relatively lacking. Especially in the aspect ...

AI Technical Summary

Problems solved by technology

Although fractal dimension and texture analysis have achieved certain results in the characterization of material morphology, there have been no related reports on more in-depth and accurate classification and identification.

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