Graph-based keyword spotting in historical documents using context-aware Hausdorff edit distance

Stauffer, Michael (University of Applied Sciences and Arts Northwestern Switzerland, Institute for Information Systems, Olten, Switzerland ; University of Pretoria, Department of Informatics, Pretoria, South Africa) ; Fischer, Andreas (School of Engineering and Architecture (HEIA-FR), HES-SO // University of Applied Sciences Western Switzerland ; University of Fribourg, Fribourg, Switzerland) ; Riesen, Kaspar (University of Applied Sciences and Arts Northwestern Switzerland, Institute for Information Systems, Olten, Switzerland)

Scanned handwritten historical documents are often not well accessible due to the limited feasibility of automatic full transcriptions. Thus, Keyword Spotting (KWS) has been proposed as an alternative to retrieve arbitrary query words from this kind of documents. In the present paper, word images are represented by means of graphs. That is, a graph is used to represent the inherent topological characteristics of handwriting. The actual keyword spotting is then based on matching a query graph with all document graphs. In particular, we make use of a fast graph matching algorithm that considers the contextual substructure of nodes. The motivation for this inclusion of node context is to increase the overall KWS accuracy. In an experimental evaluation on four historical documents, we show that the proposed procedure clearly outperforms diverse other template-based reference systems. Moreover, our novel framework keeps up or even outperforms many state-of-the-art learning-based KWS approaches.


Keywords:
Conference Type:
full paper
Faculty:
Ingénierie et Architecture
School:
HEIA-FR
Institute:
iCoSys - Institut des systèmes complexes
Subject(s):
Ingénierie
Publisher:
Vienna, Austria, 24-27 April 2018
Date:
2018-04
Vienna, Austria
24-27 April 2018
Pagination:
6 p.
Published in:
Proceedings of DAS 2018 : 13th IAPR International Workshop on Document Analysis Systems, 24-27 April 2018, Vienna, Austria
DOI:
ISBN:
978-1-5386-3346-5
External resources:
Appears in Collection:

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 Record created 2019-02-26, last modified 2019-03-05

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