PT Unknown
AU Alicia Fornes
   Volkmar Frinken
   Andreas Fischer
   Jon Almazan
   G. Jackson
   Horst Bunke
TI A Keyword Spotting Approach Using Blurred Shape Model-Based Descriptors
BT Proceedings of the 2011 Workshop on Historical Document Imaging and Processing
PY 2011
BP 83
EP 90
DI 10.1145/2037342.2037356
AB The automatic processing of handwritten historical documents is considered a hard problem in pattern recognition.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.
ER