%0 Conference Proceedings
%4 sid.inpe.br/sibgrapi@80/2009/08.26.13.24
%2 sid.inpe.br/sibgrapi@80/2009/08.26.13.24.25
%@doi 10.1109/SIBGRAPI.2009.31
%T Detecting Buildings in Historical Photographs Using Bag-of-Keypoints
%D 2009
%A Batista, Natália Cosse,
%A Lopes, Ana Paula Brandão,
%A Araújo, Arnaldo de Albuquerque,
%@affiliation Federal University of Minas Gerais (UFMG)
%@affiliation Federal University of Minas Gerais (UFMG) and State University of Santa Cruz (UESC)
%@affiliation Federal University of Minas Gerais (UFMG)
%E Nonato, Luis Gustavo,
%E Scharcanski, Jacob,
%B Brazilian Symposium on Computer Graphics and Image Processing, 22 (SIBGRAPI)
%C Rio de Janeiro, RJ, Brazil
%8 11-14 Oct. 2009
%I IEEE Computer Society
%J Los Alamitos
%S Proceedings
%K historical photographs, image classification, buildings recognition, bag-of-keypoints.
%X The strategies for the preservation of historical documents can include their digitization, which is an effective way to make them publicly available while preventing degradation of the original sources. The Arquivo Público Mineiro (APM), the Archives of the State of Minas Gerais, has a collection of historical photographs from Brazil, and some of them have been digitized. The availability of digital copies of historical photographs makes it possible to apply Content- Based Image Retrieval (CBIR) techniques to alleviate the huge manual effort that is put nowadays into their description and indexing. On the other side, such images are usually more challenging than modern photographs, because of the poor quality of the originals and several degradation effects. In this work, it is proposed a technique based on a bag-of-keypoints representation to identify images containing buildings in the APM photographic collection. The bag-of-keypoints is an efficient image representation technique, which has been proved robust to occlusion and variations due to pose, scale, illumination and several transformations. Experiments were performed on the images from the APM collection, to classify them between building and non-building, using bag-of- keypoints representations of those images. Results show that, despite of the poor quality of the images, the bag-of-keypoints representation is able to provide good detection rates, indicating the suitability of the proposed method for the task.
%@language en
%3 PID949959.pdf