Symbol Detection Using Region Adjacency Graphs and Integer Linear Programming
| Autor: | Yves Lecourtier, Hervé Locteau, Pierre Héroux, Sébastien Adam, Pierre Le Bodic, Arnaud Knippel |
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| Přispěvatelé: | Laboratoire de Recherche en Informatique (LRI), Université Paris-Sud - Paris 11 (UP11)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS), Querying Graphics through Analysis and Recognition (QGAR), INRIA Lorraine, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique de Lorraine (INPL)-Université Nancy 2-Université Henri Poincaré - Nancy 1 (UHP)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique de Lorraine (INPL)-Université Nancy 2-Université Henri Poincaré - Nancy 1 (UHP), 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), Laboratoire de Mathématiques de l'INSA de Rouen Normandie (LMI), Institut National des Sciences Appliquées (INSA)-Normandie Université (NU)-Institut National des Sciences Appliquées (INSA)-Normandie Université (NU), Computer Vision Center, International Association for Pattern Recognition TC-10 and TC-11, Institut National de Recherche en Informatique et en Automatique (Inria)-Université Henri Poincaré - Nancy 1 (UHP)-Université Nancy 2-Institut National Polytechnique de Lorraine (INPL)-Centre National de la Recherche Scientifique (CNRS)-Université Henri Poincaré - Nancy 1 (UHP)-Université Nancy 2-Institut National Polytechnique de Lorraine (INPL)-Centre National de la Recherche Scientifique (CNRS), Université Le Havre Normandie (ULH), Normandie Université (NU)-Normandie Université (NU)-Université de Rouen Normandie (UNIROUEN), Normandie Université (NU)-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) |
| Rok vydání: | 2009 |
| Předmět: |
Linear programming
business.industry Computer science Feature vector [INFO.INFO-DS]Computer Science [cs]/Data Structures and Algorithms [cs.DS] Subgraph isomorphism problem [INFO.INFO-LO]Computer Science [cs]/Logic in Computer Science [cs.LO] 020207 software engineering Graph theory Pattern recognition 02 engineering and technology Graph Vertex (geometry) Combinatorics [INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV] [INFO.INFO-IR]Computer Science [cs]/Information Retrieval [cs.IR] 0202 electrical engineering electronic engineering information engineering Adjacency list 020201 artificial intelligence & image processing Induced subgraph isomorphism problem Artificial intelligence Graph isomorphism business Integer programming MathematicsofComputing_DISCRETEMATHEMATICS |
| Zdroj: | ICDAR International Conference on Document Analysis and Recognition International Conference on Document Analysis and Recognition, Computer Vision Center, Jul 2009, Barcelona, Spain. 5 p., ⟨10.1109/ICDAR.2009.202⟩ |
| DOI: | 10.1109/icdar.2009.202 |
| Popis: | International audience; In this paper, we tackle the problem of localizing graphical symbols on complex technical document images by using an original approach to solve the subgraph isophism problem. In the proposed system, document and symbol images are represented by vector-attributed Region Adjacency Graphs (RAG) which are extracted by a segmentation process and feature extractors. Vertices representing regions are labeled with shape descriptors whereas edges are labeled with feature vector representing topological relations between the regions. Then, in order to search the instances of a model graph describing a particular symbol in a large graph corresponding to a whole document, we model the subgraph isomorphism problem as an Integer Linear Program (ILP) which enables to be error-tolerant on vectorial labels. The problem is then solved using a free efficient solver called SYMPHONY. The whole system is evaluated on a set of synthetic documents. |
| Databáze: | OpenAIRE |
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