Curvelets Based Feature Extraction of Handwritten Shapes for Ancient Manuscripts Classification

Guillaume Joutel 1 Véronique Eglin 1 Stéphane Bres 1 Hubert Emptoz 1
1 imagine - Extraction de Caractéristiques et Identification
LIRIS - Laboratoire d'InfoRmatique en Image et Systèmes d'information
Abstract : 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.
Type de document :
Communication dans un congrès
Document Recognition and Retrieval XIV, Jan 2007, San Jose, United States. SPIE, pp.0D12, 2007
Liste complète des métadonnées

https://hal.archives-ouvertes.fr/hal-01501798
Contributeur : Équipe Gestionnaire Des Publications Si Liris <>
Soumis le : mardi 4 avril 2017 - 15:45:12
Dernière modification le : mercredi 5 avril 2017 - 01:07:53

Identifiants

  • HAL Id : hal-01501798, version 1

Collections

Citation

Guillaume Joutel, Véronique Eglin, Stéphane Bres, Hubert Emptoz. Curvelets Based Feature Extraction of Handwritten Shapes for Ancient Manuscripts Classification. Document Recognition and Retrieval XIV, Jan 2007, San Jose, United States. SPIE, pp.0D12, 2007. <hal-01501798>

Partager

Métriques

Consultations de la notice

104