@InProceedings{HongxingGao2013,
author="Hongxing Gao
and Mar{\c{c}}al Rusi{\~n}ol
and Dimosthenis Karatzas
and Josep Llados
and Tomokazu Sato
and Masakazu Iwamura
and Koichi Kise",
title="Key-region detection for document images -applications to administrative document retrieval",
booktitle="12th International Conference on Document Analysis and Recognition",
year="2013",
pages="230--234",
abstract="In this paper we argue that a key-region detector designed to take into account the special characteristics of document images can result in the detection of less and more meaningful key-regions. We propose a fast key-region detector able to capture aspects of the structural information of the document, and demonstrate its efficiency by comparing against standard detectors in an administrative document retrieval scenario. We show that using the proposed detector results to a smaller number of detected key-regions and higher performance without any drop in speed compared to standard state of the art detectors.",
optnote="DAG; 600.056; 600.045",
optnote="exported from refbase (http://refbase.cvc.uab.es/show.php?record=2293), last updated on Thu, 10 Nov 2016 12:09:48 +0100",
issn="1520-5363",
doi="10.1109/ICDAR.2013.53",
file=":http://refbase.cvc.uab.es/files/GRK2013b.pdf:PDF"
}