%0 Conference Proceedings
%T Embedding Document Structure to Bag-of-Words through Pair-wise Stable Key-regions
%A Hongxing Gao
%A Marçal Rusiñol
%A Dimosthenis Karatzas
%A Josep Llados
%B 22nd International Conference on Pattern Recognition
%D 2014
%F Hongxing Gao2014
%O DAG; 600.056; 600.061; 600.077
%O exported from refbase (http://refbase.cvc.uab.es/show.php?record=2497), last updated on Fri, 23 Oct 2015 13:42:51 +0200
%X Since the document structure carries valuable discriminative information, plenty of efforts have been made for extracting and understanding document structure among which layout analysis approaches are the most commonly used. In this paper, Distance Transform based MSER (DTMSER) is employed to efficiently extract the document structure as a dendrogram of key-regions which roughly correspond to structural elements such as characters, words and paragraphs. Inspired by the Bagof Words (BoW) framework, we propose an efficient method for structural document matching by representing the document image as a histogram of key-region pairs encoding structural relationships.Applied to the scenario of document image retrieval, experimental results demonstrate a remarkable improvement when comparing the proposed method with typical BoW and pyramidal BoW methods.
%U http://refbase.cvc.uab.es/files/GRK2014b.pdf
%U http://dx.doi.org/10.1109/ICPR.2014.500
%P 2903-2908