Hierarchical entropy and domain interaction to understand the structure in an image
This work addresses the problem of image structure interpretation for researchers in computer vision or art analysis, but it appears incremental as it builds on existing entropy concepts without claiming major breakthroughs.
The study tackled the problem of interpreting image structures by introducing a model with two hierarchies in information entropy and using hierarchical entropy and domain interaction indicators, which change with region and component sizes; experiments qualitatively evaluated these indicators and applied them to analyze Vermeer's painting and image segmentation results.
In this study, we devise a model that introduces two hierarchies into information entropy. The two hierarchies are the size of the region for which entropy is calculated and the size of the component that determines whether the structures in the image are integrated or not. And this model uses two indicators, hierarchical entropy and domain interaction. Both indicators increase or decrease due to the integration or fragmentation of the structure in the image. It aims to help people interpret and explain what the structure in an image looks like from two indicators that change with the size of the region and the component. First, we conduct experiments using images and qualitatively evaluate how the two indicators change. Next, we explain the relationship with the hidden structure of Vermeer's girl with a pearl earring using the change of hierarchical entropy. Finally, we clarify the relationship between the change of domain interaction and the appropriate segment result of the image by an experiment using a questionnaire.