Textural image classification of foams based on variographic analysis

Abstract

Froths can be characterised according to several features, such as colour, bubble size distribution, velocity, mobility or texture. In the case of texture, there are some alternatives that can be used to analyse and classify them, like the texture spectrum analysis, the grey-level co-occurrence matrix, or the wavelet texture analysis. In this work, a variogram-based technique is introduced. Variograms are a widely used geostatistical technique to describe the degree of spatial dependence between sample values as separation between them increases, and have been used before to analyse textures in applications that range from microscopy to satellite images. The purpose of the current work is to introduce the variogram-based technique to compare and classify foams (water-air froths) according to their texture, and studying the effect of frother type on the texture of foams generated in a quasi-2D cell and in a laboratory column. In the case of the quasi-2D foams, the variogram-based textural classification algorithm was able to classify foam images according to the frother used, with an accuracy of 88.9%. In the case of the foam images generated in the laboratory column, the results suggest that foam texture is mainly defined by froth type, with some effect of foam height. The column foam images did not show similar characteristics when grouped by foam gas holdup, which was confirmed with the variogram-based textural analysis.