Ameri, Mohammad RezaStauffer, MichaelRiesen, KasparBui, Tien DaiFischer, Andreas2019-09-092019-04Ameri, M.R., Stauffer, M., Riesen, K. et al. 2019, 'Graph-based keyword spotting in historical manuscripts using Hausdorff edit distance', Pattern Recognition Letters, vol. 121, pp. 61-67.0167-8655 (print)1872-7344 (online)10.1016/j.patrec.2018.05.003http://hdl.handle.net/2263/71298Keyword spotting enables content-based retrieval of scanned historical manuscripts using search terms, which, in turn, facilitates the indexation in digital libraries. Recent approaches include graph-based representations that capture the complex structure of handwriting. However, the high representational power of graphs comes at the cost of high computational complexity for graph matching. In this article, we investigate the potential of Hausdorff edit distance (HED) for keyword spotting. It is an efficient quadratic-time approximation of the graph edit distance. In a comprehensive experimental evaluation with four types of handwriting graphs and four benchmark datasets (George Washington, Parzival, Botany, and Alvermann Konzilsprotokolle), we demonstrate a strong performance of the proposed HED-based method when compared with the state of the art, both, in terms of precision and speed.en© 2018 Elsevier B.V. All rights reserved. Notice : this is the author’s version of a work that was accepted for publication in Pattern Recognition Letters. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. A definitive version was subsequently published in Pattern Recognition Letters, vol. 121, pp. 61-67, 2019. doi : 10.1016/j.patrec.2018.05.003.Hausdorff edit distance (HED)Keyword spottingHandwriting graphsGraph matchingPostprint Article