%0 Conference Proceedings
%T A Coarse-to-Fine Approach for Handwritten Word Spotting in Large Scale Historical Documents Collection
%A Jon Almazan
%A David Fernandez
%A Alicia Fornes
%A Josep Llados
%A Ernest Valveny
%B 13th International Conference on Frontiers in Handwriting Recognition
%D 2012
%@ 978-1-4673-2262-1
%F Jon Almazan2012
%O DAG
%O exported from refbase (http://refbase.cvc.uab.es/show.php?record=1983), last updated on Tue, 18 Oct 2016 13:21:50 +0200
%X In this paper we propose an approach for word spotting in handwritten document images. We state the problem from a focused retrieval perspective, i.e. locating instances of a query word in a large scale dataset of digitized manuscripts. We combine two approaches, namely one based on word segmentation and another one segmentation-free. The first approach uses a hashing strategy to coarsely prune word images that are unlikely to be instances of the query word. This process is fast but has a low precision due to the errors introduced in the segmentation step. The regions containing candidate words are sent to the second process based on a state of the art technique from the visual object detection field. This discriminative model represents the appearance of the query word and computes a similarity score. In this way we propose a coarse-to-fine approach achieving a compromise between efficiency and accuracy. The validation of the model is shown using a collection of old handwritten manuscripts. We appreciate a substantial improvement in terms of precision regarding the previous proposed method with a low computational cost increase.
%U http://refbase.cvc.uab.es/files/AFF2012a.pdf
%U http://dx.doi.org/10.1109/ICFHR.2012.151
%P 453-458