The aim of this scientific work is to propose a suitable assistance tool for palaeographers and
historians to help them in their intuitive and empirical work of identification of writing styles (for medieval
handwritings) and authentication of writers (for humanistic manuscripts). We propose a global approach of
writers' classification based on Curvelets based features in relation with two discriminative shapes properties, the
curvature and the orientation. Those features are revealing of structural and directional micro-shapes and also of
concavity that captures the finest variations in the contour. The Curvelets based analysis leads to the construction
of a compact Log-polar signature for each writing. The relevance of the signature is quantified with a CBIR
(content based image retrieval) system that compares request images and database images candidates. The main
experimental results are very promising and show 78% of good retrieval (as precision) on the Middle-Ages
database and 89% on the humanistic database.
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