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Using SR-tree in a Content-based and Location-based Image Retrieval System

This paper presents an approach for combining content-based and location-based information in an image retrieval system. With the performance for nearest neighbour queries in the area of multidimensional data and for spatial data structuring, the SR-tree (Katayama and Satoh, 1997) structure is chosen for structuring the images simultaneously in location space and visual content space. The proposed approach also uses the SR-tree structure to organize various geographic objects of a Geographic Information System (GIS). We apply then this approach to a decision-aid system in a situation of post-natural disaster in which images describe different disasters and geographic objects are monuments registered in GIS data in the form of polygons. The proposed system aims at finding emergencies in the city after a natural disaster and giving them an emergency level. Some scenarios showing the interest of using content-based and location-based search in different ways are also presented and tested in the developed system.