Graph-based keyword spotting in historical manuscripts using Hausdorff edit distance

•Graph-based keyword spotting method using Hausdorff edit distance.•Flexible: matching arbitrary graphs with any label alphabets.•Efficient: quadratic time complexity with respect to graph size.•Effective: outperforms other template-based spotting methods.•Evaluation on four benchmark datasets including recent competition. Keyword 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.