Handwritten Word Spotting by Inexact Matching of Grapheme Graphs
Pau Riba
author
Josep Llados
author
Alicia Fornes
author
2015
This paper presents a graph-based word spotting for handwritten documents. Contrary to most word spotting techniques, which use statistical representations, we propose a structural representation suitable to be robust to the inherent deformations of handwriting. Attributed graphs are constructed using a part-based approach. Graphemes extracted from shape convexities are used as stable units of handwriting, and are associated to graph nodes. Then, spatial relations between them determine graph edges. Spotting is defined in terms of an error-tolerant graph matching using bipartite-graph matching algorithm. To make the method usable in large datasets, a graph indexing approach that makes use of binary embeddings is used as preprocessing. Historical documents are used as experimental framework. The approach is comparable to statistical ones in terms of time and memory requirements, especially when dealing with large document collections.
DAG; 600.077; 600.061; 602.006
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text
http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=7321714
http://refbase.cvc.uab.es/files/RLF2015b.pdf
http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=7321714
10.1109/ICDAR.2015.7333868
Admin @ si @ RLF2015b
13th International Conference on Document Analysis and Recognition ICDAR2015
ICDAR
2015
conference publication
781
785