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Author |
Partha Pratim Roy; Umapada Pal; Josep Llados |
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Title |
Recognition of Multi-oriented Touching Characters in Graphical Documents |
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Conference Article |
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Year |
2008 |
Publication |
Computer Vision, Graphics & Image Processing, 2008. Sixth Indian Conference on, |
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16 |
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297–304 |
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ICVGIP ’08 |
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DAG |
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DAG @ dag @ RPL2008c |
Serial |
1080 |
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Author |
Josep Llados; Marçal Rusiñol |
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Title |
Graphics Recognition Techniques |
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Book Chapter |
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Year |
2014 |
Publication |
Handbook of Document Image Processing and Recognition |
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Volume |
D |
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489-521 |
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Keywords |
Dimension recognition; Graphics recognition; Graphic-rich documents; Polygonal approximation; Raster-to-vector conversion; Texture-based primitive extraction; Text-graphics separation |
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Abstract |
This chapter describes the most relevant approaches for the analysis of graphical documents. The graphics recognition pipeline can be splitted into three tasks. The low level or lexical task extracts the basic units composing the document. The syntactic level is focused on the structure, i.e., how graphical entities are constructed, and involves the location and classification of the symbols present in the document. The third level is a functional or semantic level, i.e., it models what the graphical symbols do and what they mean in the context where they appear. This chapter covers the lexical level, while the next two chapters are devoted to the syntactic and semantic level, respectively. The main problems reviewed in this chapter are raster-to-vector conversion (vectorization algorithms) and the separation of text and graphics components. The research and industrial communities have provided standard methods achieving reasonable performance levels. Hence, graphics recognition techniques can be considered to be in a mature state from a scientific point of view. Additionally this chapter provides insights on some related problems, namely, the extraction and recognition of dimensions in engineering drawings, and the recognition of hatched and tiled patterns. Both problems are usually associated, even integrated, in the vectorization process. |
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Springer London |
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D. Doermann; K. Tombre |
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978-0-85729-858-4 |
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DAG; 600.077 |
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Admin @ si @ LlR2014 |
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2380 |
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Author |
Muhammad Muzzamil Luqman; Thierry Brouard; Jean-Yves Ramel; Josep Llados |
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Title |
Recherche de sous-graphes par encapsulation floue des cliques d'ordre 2: Application à la localisation de contenu dans les images de documents graphiques |
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Conference Article |
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Year |
2012 |
Publication |
Colloque International Francophone sur l'Écrit et le Document |
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149-162 |
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CIFED |
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DAG |
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Admin @ si @ LBR2012 |
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2382 |
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Author |
Jose Antonio Rodriguez; Gemma Sanchez; Josep Llados |
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Title |
Categorization of Digital Ink Elements using Spectral Features |
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Book Chapter |
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Year |
2008 |
Publication |
Graphics Recognition: Recent Advances and New Opportunities |
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Volume |
5046 |
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Pages |
188–198 |
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Springer–Verlag |
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W. Liu, J. Llados, J.M. Ogier |
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LNCS |
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DAG |
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DAG @ dag @ RSL2008 |
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1099 |
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Author |
Josep Llados; Dimosthenis Karatzas; Joan Mas; Gemma Sanchez |
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Title |
A Generic Architecture for the Conversion of Document Collections into Semantically Annotated Digital Archives |
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Journal |
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Year |
2008 |
Publication |
Journal of Universal Computer Science |
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14 |
Issue |
18 |
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2912–2935 |
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Keywords |
Median Graph, Graph Embedding, Graph Matching, Structural Pattern Recognition |
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DAG |
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DAG @ dag @ LKM2008 |
Serial |
1142 |
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Author |
Miquel Ferrer; Ernest Valveny; F. Serratosa |
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Title |
Median Graphs: A Genetic Approach based on New Theoretical Properties |
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Journal Article |
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Year |
2009 |
Publication |
Pattern Recognition |
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PR |
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42 |
Issue |
9 |
Pages |
2003–2012 |
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Keywords |
Median graph; Genetic search; Maximum common subgraph; Graph matching; Structural pattern recognition |
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Abstract |
Given a set of graphs, the median graph has been theoretically presented as a useful concept to infer a representative of the set. However, the computation of the median graph is a highly complex task and its practical application has been very limited up to now. In this work we present two major contributions. On one side, and from a theoretical point of view, we show new theoretical properties of the median graph. On the other side, using these new properties, we present a new approximate algorithm based on the genetic search, that improves the computation of the median graph. Finally, we perform a set of experiments on real data, where none of the existing algorithms for the median graph computation could be applied up to now due to their computational complexity. With these results, we show how the concept of the median graph can be used in real applications and leaves the box of the only-theoretical concepts, demonstrating, from a practical point of view, that can be a useful tool to represent a set of graphs. |
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DAG |
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DAG @ dag @ FVS2009b |
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1167 |
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Author |
Marçal Rusiñol; Agnes Borras; Josep Llados |
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Title |
Relational Indexing of Vectorial Primitives for Symbol Spotting in Line-Drawing Images |
Type |
Journal Article |
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Year |
2010 |
Publication |
Pattern Recognition Letters |
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PRL |
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Volume |
31 |
Issue |
3 |
Pages |
188–201 |
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Keywords |
Document image analysis and recognition, Graphics recognition, Symbol spotting ,Vectorial representations, Line-drawings |
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Abstract |
This paper presents a symbol spotting approach for indexing by content a database of line-drawing images. As line-drawings are digital-born documents designed by vectorial softwares, instead of using a pixel-based approach, we present a spotting method based on vector primitives. Graphical symbols are represented by a set of vectorial primitives which are described by an off-the-shelf shape descriptor. A relational indexing strategy aims to retrieve symbol locations into the target documents by using a combined numerical-relational description of 2D structures. The zones which are likely to contain the queried symbol are validated by a Hough-like voting scheme. In addition, a performance evaluation framework for symbol spotting in graphical documents is proposed. The presented methodology has been evaluated with a benchmarking set of architectural documents achieving good performance results. |
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Elsevier |
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DAG |
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DAG @ dag @ RBL2010 |
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1177 |
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Author |
Sergio Escalera; Alicia Fornes; O. Pujol; Petia Radeva; Gemma Sanchez; Josep Llados |
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Title |
Blurred Shape Model for Binary and Grey-level Symbol Recognition |
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Journal Article |
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Year |
2009 |
Publication |
Pattern Recognition Letters |
Abbreviated Journal |
PRL |
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30 |
Issue |
15 |
Pages |
1424–1433 |
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Abstract |
Many symbol recognition problems require the use of robust descriptors in order to obtain rich information of the data. However, the research of a good descriptor is still an open issue due to the high variability of symbols appearance. Rotation, partial occlusions, elastic deformations, intra-class and inter-class variations, or high variability among symbols due to different writing styles, are just a few problems. In this paper, we introduce a symbol shape description to deal with the changes in appearance that these types of symbols suffer. The shape of the symbol is aligned based on principal components to make the recognition invariant to rotation and reflection. Then, we present the Blurred Shape Model descriptor (BSM), where new features encode the probability of appearance of each pixel that outlines the symbols shape. Moreover, we include the new descriptor in a system to deal with multi-class symbol categorization problems. Adaboost is used to train the binary classifiers, learning the BSM features that better split symbol classes. Then, the binary problems are embedded in an Error-Correcting Output Codes framework (ECOC) to deal with the multi-class case. The methodology is evaluated on different synthetic and real data sets. State-of-the-art descriptors and classifiers are compared, showing the robustness and better performance of the present scheme to classify symbols with high variability of appearance. |
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HuPBA; DAG; MILAB |
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Call Number |
BCNPCL @ bcnpcl @ EFP2009a |
Serial |
1180 |
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Author |
Sergio Escalera; Alicia Fornes; Oriol Pujol; Alberto Escudero; Petia Radeva |
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Title |
Circular Blurred Shape Model for Symbol Spotting in Documents |
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Conference Article |
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Year |
2009 |
Publication |
16th IEEE International Conference on Image Processing |
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1985-1988 |
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Symbol spotting problem requires feature extraction strategies able to generalize from training samples and to localize the target object while discarding most part of the image. In the case of document analysis, symbol spotting techniques have to deal with a high variability of symbols' appearance. In this paper, we propose the Circular Blurred Shape Model descriptor. Feature extraction is performed capturing the spatial arrangement of significant object characteristics in a correlogram structure. Shape information from objects is shared among correlogram regions, being tolerant to the irregular deformations. Descriptors are learnt using a cascade of classifiers and Abadoost as the base classifier. Finally, symbol spotting is performed by means of a windowing strategy using the learnt cascade over plan and old musical score documents. Spotting and multi-class categorization results show better performance comparing with the state-of-the-art descriptors. |
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Cairo, Egypt |
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978-1-4244-5653-6 |
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ICIP |
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MILAB;HuPBA;DAG |
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BCNPCL @ bcnpcl @ EFP2009b |
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1184 |
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Author |
Agnes Borras; Josep Llados |
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Title |
Corest: A measure of color and space stability to detect salient regions according to human criteria |
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Conference Article |
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Year |
2009 |
Publication |
5th International Conference on Computer Vision Theory and Applications |
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204-209 |
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Lisboa, Portugal |
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978-989-8111-69-2 |
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VISAPP |
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DAG @ dag @ BoL2009 |
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1225 |
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