A bottom-up method using texture features and a graph-based representation for lettrine recognition and classification
| Autor: | Julien Lerouge, Rémy Mullot, Petra Gomez-Krämer, Pierre Héroux, Mickael Coustaty, Maroua Mehri |
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| Přispěvatelé: | Laboratoire Informatique, Image et Interaction - EA 2118 (L3I), Université de La Rochelle (ULR), Laboratoire d'Informatique, de Traitement de l'Information et des Systèmes (LITIS), Institut national des sciences appliquées Rouen Normandie (INSA Rouen Normandie), Institut National des Sciences Appliquées (INSA)-Normandie Université (NU)-Institut National des Sciences Appliquées (INSA)-Normandie Université (NU)-Université de Rouen Normandie (UNIROUEN), Normandie Université (NU)-Université Le Havre Normandie (ULH), Normandie Université (NU), Equipe Apprentissage (DocApp - LITIS), Normandie Université (NU)-Institut national des sciences appliquées Rouen Normandie (INSA Rouen Normandie), ANR-10-CORD-0020,DIGIDOC,Document Image diGitisation with Interactive DescriptiOn Capability(2010) |
| Jazyk: | angličtina |
| Rok vydání: | 2015 |
| Předmět: |
Computer science
business.industry Search engine indexing Graph based Pattern recognition Top-down and bottom-up design computer.software_genre Classification Graph [INFO.INFO-TT]Computer Science [cs]/Document and Text Processing Recognition Categorization Graph (abstract data type) Indexing Data mining Artificial intelligence Lettrine business Tex-ture computer |
| Zdroj: | International Conference on Document Analysis and Recognition (ICDAR) International Conference on Document Analysis and Recognition (ICDAR), Aug 2015, Nancy, France. pp.226-230, ⟨10.1109/ICDAR.2015.7333757⟩ ICDAR |
| DOI: | 10.1109/ICDAR.2015.7333757⟩ |
| Popis: | International audience; This article tackles some important issues relating to the analysis of a particular case of complex ancient graphic images, called " lettrines " , " drop caps " or " ornamental letters ". Our contribution focuses on proposing generic solutions for lettrine recognition and classification. Firstly, we propose a bottom-up segmentation method, based on texture, ensuring the separation of the letter from the elements of the background in an ornamental letter. Secondly, a structural representation is proposed for characterizing a lettrine. This structural representation is based on filtering automatically relevant information by extracting representative homogeneous regions from a lettrine to generate a graph-based signature. The proposed signature provides a rich and holistic description of the lettrine style by integrating varying low-level features (e.g. texture). Then, to categorize and classify lettrines with similar style, structure (i.e. ornamental background) and content (i.e. letter), a graph-matching paradigm has been carried out to compare and classify the resulting graph-based signatures. Finally, to demonstrate the robustness of the proposed solutions and provide additional insights into their accuracies, an experimental evaluation has been conducted using a relevant set of lettrine images. In addition, we compare the results achieved with those obtained using the state-of-the-art methods to illustrate the effectiveness of the proposed solutions. |
| Databáze: | OpenAIRE |
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