%0 Conference Proceedings
%T A Keyword Spotting Approach Using Blurred Shape Model-Based Descriptors
%A Alicia Fornes
%A Volkmar Frinken
%A Andreas Fischer
%A Jon Almazan
%A G. Jackson
%A Horst Bunke
%B Proceedings of the 2011 Workshop on Historical Document Imaging and Processing
%D 2011
%I ACM
%@ 978-1-4503-0916-5
%F Alicia Fornes2011
%O DAG
%O exported from refbase (http://refbase.cvc.uab.es/show.php?record=1823), last updated on Thu, 17 May 2012 10:40:37 +0200
%X The automatic processing of handwritten historical documents is considered a hard problem in pattern recognition. In addition to the challenges given by modern handwritten data, a lack of training data as well as effects caused by the degradation of documents can be observed. In this scenario, keyword spotting arises to be a viable solution to make documents amenable for searching and browsing. For this task we propose the adaptation of shape descriptors used in symbol recognition. By treating each word image as a shape, it can be represented using the Blurred Shape Model and the De-formable Blurred Shape Model. Experiments on the George Washington database demonstrate that this approach is able to outperform the commonly used Dynamic Time Warping approach.
%U http://dx.doi.org/10.1145/2037342.2037356
%P 83-90