Recuperação de imagens: similaridade parcial baseada em espectro de grafo e cor

Abstract

Traditionally, local shape descriptors or color and texture based descriptors are used to describe the content of images. Although, these solutions achieving good results, they are not able to distinguish scenes that contain objects with the same colors, but with a different spatial organization or do not supports partial matching. In this work we focus on a particular case of the partial matching that is to find individual objects in images that contain various objects. Since the color is one of the most visually distinguishable properties, we propose a new descriptor based only on color able to find pictures of objects that are contained in other images. Although our descriptor has shown better results when compared to related works, this new color descriptor is not able to discriminate objects topologically different but having the same colors. To overcome this problem, we also propose a new approach to the partial matching of images that combine color and topological features on a single descriptor. This new descriptor, first performs a simplification process of the original image, which identifies the color regions that make up the image. Then, we represent the spatial information among the color regions using a topological graph, where vertices represent the color regions and the edges represent the spatial connections between them. To calculate the descriptor from this graph representation, we use the spectral theory of graphs, avoiding the need to make a direct comparison between graphs. To support the partial matching, we propose a decomposition of the main graph into several subgraphs, and also calculate descriptors for these subgraphs.