@InProceedings{AliciaFornes2011,
author="Alicia Fornes
and Volkmar Frinken
and Andreas Fischer
and Jon Almazan
and G. Jackson
and Horst Bunke",
title="A Keyword Spotting Approach Using Blurred Shape Model-Based Descriptors",
booktitle="Proceedings of the 2011 Workshop on Historical Document Imaging and Processing",
year="2011",
publisher="ACM",
pages="83--90",
abstract="The automatic processing of handwritten historical documents is considered a hard problem in pattern recognition.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.",
optnote="DAG",
optnote="exported from refbase (http://refbase.cvc.uab.es/show.php?record=1823), last updated on Thu, 17 May 2012 10:40:37 +0200",
isbn="978-1-4503-0916-5",
doi="10.1145/2037342.2037356"
}