Um descritor de imagens baseado em particionamento extremo para busca em bases grandes e heterogêneas

Abstract

In this thesis we propose a new image descriptor that address the problem of image search in large and heterogeneous databases. This approach uses the idea of extreme partitioning to obtain the visual properties of images that will be converted into a textual description. Once the textual description is appropriately generated, traditional text-based information retrieval techniques can be used. The key point of the proposed work is escalability, given that text-based search techniques can deal with databases with millions of documents. We have carried out experiments in order to con rm the viability of our proposal. The experimental results showed that our technique reaches higher precision levels compared to other content-based image retrieval techniques in a database with more than 100,000 images.