%0 Conference Proceedings
%T A Fast Matching Algorithm for Graph-Based Handwriting Recognition
%A Andreas Fischer
%A Ching Y. Suen
%A Volkmar Frinken
%A Kaspar Riesen
%A Horst Bunke
%B 9th IAPR – TC15 Workshop on Graph-based Representation in Pattern Recognition
%D 2013
%V 7877
%I Springer Berlin Heidelberg
%@ 0302-9743
%@ 978-3-642-38220-8
%F Andreas Fischer2013
%O DAG; 600.045; 605.203
%O exported from refbase (http://refbase.cvc.uab.es/show.php?record=2294), last updated on Thu, 10 Nov 2016 11:54:48 +0100
%X The recognition of unconstrained handwriting images is usually based on vectorial representation and statistical classification. Despite their high representational power, graphs are rarely used in this field due to a lack of efficient graph-based recognition methods. Recently, graph similarity features have been proposed to bridge the gap between structural representation and statistical classification by means of vector space embedding. This approach has shown a high performance in terms of accuracy but had shortcomings in terms of computational speed. The time complexity of the Hungarian algorithm that is used to approximate the edit distance between two handwriting graphs is demanding for a real-world scenario. In this paper, we propose a faster graph matching algorithm which is derived from the Hausdorff distance. On the historical Parzival database it is demonstrated that the proposed method achieves a speedup factor of 12.9 without significant loss in recognition accuracy.
%U http://refbase.cvc.uab.es/files/FSF2013.pdf
%U http://dx.doi.org/10.1007/978-3-642-38221-5_21
%P 194-203