Pintus, RuggeroYang, YingGobbetti, EnricoRushmeier, HollyGabriele Guidi and Roberto Scopigno and Juan Barceló2016-01-062016-01-062015978-1-5090-0048-7https://doi.org/10.1109/DigitalHeritage.2015.7419446We present a completely automatic and scalable framework to perform query-by-example word-spotting on medieval manuscripts. Our system does not require any human intervention to produce a large amount of annotated training data, and it provides Computer Vision researchers and Cultural Heritage practitioners with a compact and efficient system for document analysis. We have executed the pipeline both in a single-manuscript and a cross-manuscript setup, and we have tested it on a heterogeneous set of medieval manuscripts, that includes a variety of writing styles, languages, image resolutions, levels of conservation, noise and amount of illumination and ornamentation. We also present a precision/recall based analysis to quantitatively assess the quality of the proposed algorithm.Document Layout AnalysisWordspottingMedieval Manuscript10.1109/DigitalHeritage.2015.7419446