Visual model for image analysis of material characterization and analysis method thereof

A method for analyzing images of material characterization, wherein it comprises the following steps:

• collect and mark samples of material characterization images to establish an image data set of material characterization, wherein the said image data set of material characterization comprises a first data set composed of first material characterization images marked with atomic species and crystal structure parameters, and a second data set composed of second material characterization images marked with edges and center points of microscopic particles and a third data set composed of third material characterization images marked with microstructure features;
• establish an initial neural network model, and use the image data set of material characterization to train it to obtain a neural network model based on deep learning;
• and establish a dynamic statistical model;
• input the characterization image of the material to be analyzed into the deep learning-based neural network model, and identify and analyze the output results, complete atom identification and interplanar spacing annotation, microscopic particle morphology statistics;
• and
• input the third data set or output data of the deep learning-based neural network model into the dynamic statistical model to complete tracking of microstructure motion trajectory.