PT Unknown
AU Jon Almazan
   David Fernandez
   Alicia Fornes
   Josep Llados
   Ernest Valveny
TI A Coarse-to-Fine Approach for Handwritten Word Spotting in Large Scale Historical Documents Collection
BT 13th International Conference on Frontiers in Handwriting Recognition
PY 2012
BP 453
EP 458
DI 10.1109/ICFHR.2012.151
AB 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.
ER