A Study of the Multivariate Image Analysis Method Combining Texture with Colour Features

Abstract

Multivariate image analysis is a method of analysing multiple images by using principal component analysis, which analyses the information between multiple spectra of multiple images, and also means the colour information in RGB terms. While multivariate image analysis can get the colour features of an image, analysis of the texture features of an image is missing. This paper proposes a dual-feature multivariate image analysis method based on the grey-level co-occurrence matrix and the sliding window method to extract texture feature information in images and fuse it with colour feature information. This approach makes up for the shortcomings of the multivariate image analysis method for the analysis of texture feature information in images. The experiment on images with both texture features and colour features shows that the method proposed in this paper is effective.