Image analyzer for material structure using fourier transform and principal component analysis

Abstract

For easy visualization of features of an image representing a structure of a material, an image analyzer includes a transformer that performs a Fourier transform on each of a plurality of original images representing a structure of a material and acquires a plurality of power spectra; an analyzer that performs principal component analysis on the plurality of power spectra and acquires principal components and principal component scores; and a reconstructor that reconstructs an image based on the principal components and principal component scores and outputs a feature image representing features of the original image. The reconstructor generates a difference image based on a reconstructed changed image obtained by changing one or more of the principal component scores and a reference image, and outputs the generated difference image as the feature image. The principal component score to be changed may be determined using a trained regression/classification model constructed by machine learning.