Evaluation and assessment of homogeneity in images. Part 2: Homogeneity assessment on single channel non-binary images. Blending end-point detection as example

This paper demonstrates that the use of the homogeneity curve approach introduced in the first part of this work for assessing the unique homogeneity percentage (%H) can also be applied in single channel non-binary (SCNB) images (a.k.a grayscale images) analysis. In order to address a more general homogeneity index approach for SCNB images, more realistic assumptions such as the presence of divisible objects or the mixture of different objects in the same pixel, are considered. The proposed parameter, %H, is an absolute homogeneity percentage that uses only the self-contained information of one image, with no need for additional modelling steps, as described in most of the works addressing the homogeneity assessment. To demonstrate it, two cases have been evaluated. The first case validates the %H by assessing the homogeneity in images with different textures (distribution of objects). In the second case, the reliability of assessing the evolution of homogeneity and providing an end-point detection in blending process trials done at small scale has been evaluated. The results obtained in the current work show the high potential when using the %H for industrial applications where the distributional homogeneity represents a critical process parameter to ensure the quality of the final product.