%0 Conference Proceedings
%4 sid.inpe.br/sibgrapi@80/2009/08.17.17.33
%2 sid.inpe.br/sibgrapi@80/2009/08.17.17.33.31
%@doi 10.1109/SIBGRAPI.2009.40
%T Automatic discrimination between printed and handwritten text in documents
%D 2009
%A Silva, Lincoln Faria da,
%A Sanchez, Angel,
%A Conci, Aura,
%@affiliation UFF
%@affiliation Universidad Rey Juan Carlos
%@affiliation UFF
%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 Data Mining, document analysis, text identification, optical characters recognition, Machine Vision.
%X Recognition techniques for printed and handwritten text in scanned documents are significantly different. In this paper we address the problem of identifying each type. We can list at least four steps: digitalization, preprocessing, feature extraction and decision or classification. A new aspect of our approach is the use of data mining techniques on the decision step. A new set of features extracted of each word is proposed as well. Classification rules are mining and used to discern printed text from handwritten. The proposed system was tested in two public image databases. All possible measures of efficiency were computed achieving on every occasion quantities above 80%.
%@language en
%3 57993.pdf