Porous material hole automatic measurement method based on scanning electron microscope image segmentation

Abstract

The invention belongs to the technical field of image processing, and discloses a porous material hole automatic measurement method based on scanning electron microscope image segmentation, which comprises the following steps of 1, initializing parameters; 2, filtering processing; 3, obtaining a potential clustering number through the characteristic value information; 4, calculating histogram information of the filtered image; 5, completing image segmentation by using a fast fuzzy clustering algorithm; 6, extracting data distribution corresponding to the minimum clustering center as hole output to obtain a binary hole image; 7, performing morphological filling operation on the binary hole image; 8, automatically classifying the holes according to areas by utilizing multi-scale morphological closed reconstruction; and 9, counting the number, the area ratio and the actual average area of holes of different grades in the porous material. According to the method, automatic measurement andclassification of the holes of the porous material are realized, the porous material can be objectively evaluated, and an ideal image segmentation effect can be directly obtained.

Description

technical field [0001] The invention belongs to the technical field of image processing, and in particular relates to an automatic measurement method for holes in porous materials based on scanning electron microscope image segmentation. Background technique [0002] Scanning electron microscope (SEM) is a surface analysis technique with a very wide range of applications. It mainly uses secondary electron signals to scan the surface of the sample to obtain corresponding high-magnification images. The analysis scale can reach the nanometer level and can effectively observe the surface of the sample Microstructure and state, so it has been widely used in materials, chemical industry, food, machinery and other fields. [0003] SEM can present the microscopic morphology of porous materials, and it is helpful to understand the physical and chemical properties of porous materials, such as surface adsorption and wear resistance, by counting the pore characteristics on the surface o...

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Problems solved by technology

[0008]However, due to the fuzzy hole outline and complex background in the SEM images of porous materials, the mainstream improved algorithms FLIL, FRFCM and DSFCM-N cannot directly obtain ideal images In addition, the existing clustering-based image segmentation algorithm needs to manually set the number of clusters, which is low in practicability. How to realize the automatic segmentation of SEM images of porous materials to solve the objective statistics of pore information In order to realize the objective evaluation of porous materials, further research is needed

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