Material surface topological structure grading quantitative analysis method and application

Abstract

The invention belongs to the technical field of image processing and material surface topological structure analysis and discloses a hierarchical quantitative analysis method for a topological structure on a surface of a material and an application. The method is characterized in that the grayscale value information of pixel points in a scanning electron microscope high-resolution image is obtained through an image processing technology, and multi-scale quantitative analysis and surface roughness analysis under different scales can be carried out on the surface topography of a sample by analyzing the grayscale characteristics of all the pixel points in the image. The method is advantaged in that large-scale, micron-scale and nano-scale graded quantitative statistical analysis can be quickly carried out on the surface topography structure of the material, the structural information of accurate quantification of each scale structural feature of the complex surface is obtained, multi-scale quantitative analysis of the complex surface is achieved, the multi-scale roughness analysis result is obtained, the covering effect of a large-scale structure on a small-scale structure in a conventional statistical analysis method is reduced, and therefore accurate quantification multi-scale analysis of the complex surface is achieved, and the method is wide in application range and high in operability.

Description

technical field [0001] The invention belongs to the technical field of image processing and material surface topological structure analysis, and in particular relates to a hierarchical and quantitative analysis method and application of material surface topological structure. Background technique [0002] Based on the existing characterization methods, the characterization and description of multi-scale complex surface structure features is too general and abstract, such as the descriptive characterization of electron scanning microscopic images, such as micro-holes, irregular craters, etc., which are intuitive but not quantitative. Both the roughness analyzer and the topology analyzer can give quantitative results, but these results are the average value of each scale structure of the complex surface. Therefore, there are large-scale structures such as micron-scale structure characteristics from the results. Covering small-scale features such as submicron scale and nanoscal...

AI Technical Summary

Problems solved by technology

[0004] Through the above analysis, the problems and defects of the existing technology are: the existing technology cannot accurately describe and characterize the multi-scale complex surface according to the quantitative structural features on each scale

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