Characterization of spatiotemporal stress distribution during food fracture by image texture analysis methods Original Research Article

This study focused on finding the potential of image texture analysis for determining the spatiotemporal fracture behavior of crispy or crunchy food products. Two-dimensional stress distribution maps were obtained during compression failure of six dry-crisp samples at four loading stages. Applying gray-level co-occurrence matrix statistics to the stress distribution maps, four major textural features were extracted, which represent the spatial pattern of the stress intensity. Stress distribution maps for the samples were classified into original classes depending on their image textural features, using a canonical discriminant analysis with an accuracy of 99%. Local variations in stress intensity and the existence of areas with the same stress intensity at higher loading stages were critical spatial factors in discriminating among the different samples. In addition to spatial factors, temporal changes in image textural features during loading also provided information necessary for sample identification. This application of image texture analysis to stress distribution maps reveals the characteristics of spatiotemporal stress distribution accompanying the dynamic fracture process for crispy or crunchy samples.