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Muhammad Muzzamil Luqman, Thierry Brouard, Jean-Yves Ramel and Josep Llados. 2010. A Content Spotting System For Line Drawing Graphic Document Images. 20th International Conference on Pattern Recognition.3420–3423.
Abstract: We present a content spotting system for line drawing graphic document images. The proposed system is sufficiently domain independent and takes the keyword based information retrieval for graphic documents, one step forward, to Query By Example (QBE) and focused retrieval. During offline learning mode: we vectorize the documents in the repository, represent them by attributed relational graphs, extract regions of interest (ROIs) from them, convert each ROI to a fuzzy structural signature, cluster similar signatures to form ROI classes and build an index for the repository. During online querying mode: a Bayesian network classifier recognizes the ROIs in the query image and the corresponding documents are fetched by looking up in the repository index. Experimental results are presented for synthetic images of architectural and electronic documents.
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Jaume Gibert, Ernest Valveny and Horst Bunke. 2010. Graph of Words Embedding for Molecular Structure-Activity Relationship Analysis. 15th Iberoamerican Congress on Pattern Recognition.30–37. (LNCS.)
Abstract: Structure-Activity relationship analysis aims at discovering chemical activity of molecular compounds based on their structure. In this article we make use of a particular graph representation of molecules and propose a new graph embedding procedure to solve the problem of structure-activity relationship analysis. The embedding is essentially an arrangement of a molecule in the form of a vector by considering frequencies of appearing atoms and frequencies of covalent bonds between them. Results on two benchmark databases show the effectiveness of the proposed technique in terms of recognition accuracy while avoiding high operational costs in the transformation.
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Oriol Ramos Terrades, N. Serrano, Albert Gordo, Ernest Valveny and Alfons Juan-Ciscar. 2010. Interactive-predictive detection of handwritten text blocks. 17th Document Recognition and Retrieval Conference, part of the IS&T-SPIE Electronic Imaging Symposium.75340Q–75340Q–10.
Abstract: A method for text block detection is introduced for old handwritten documents. The proposed method takes advantage of sequential book structure, taking into account layout information from pages previously transcribed. This glance at the past is used to predict the position of text blocks in the current page with the help of conventional layout analysis methods. The method is integrated into the GIDOC prototype: a first attempt to provide integrated support for interactive-predictive page layout analysis, text line detection and handwritten text transcription. Results are given in a transcription task on a 764-page Spanish manuscript from 1891.
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Albert Gordo and Florent Perronnin. 2010. A Bag-of-Pages Approach to Unordered Multi-Page Document Classification. 20th International Conference on Pattern Recognition.1920–1923.
Abstract: We consider the problem of classifying documents containing multiple unordered pages. For this purpose, we propose a novel bag-of-pages document representation. To represent a document, one assigns every page to a prototype in a codebook of pages. This leads to a histogram representation which can then be fed to any discriminative classifier. We also consider several refinements over this initial approach. We show on two challenging datasets that the proposed approach significantly outperforms a baseline system.
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Debora Gil, Jordi Gonzalez and Gemma Sanchez, eds. 2007. Computer Vision: Advances in Research and Development. Bellaterra (Spain), UAB. (2.)
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Gemma Sanchez, Josep Llados and Enric Marti. 1997. A string-based method to recognize symbols and structural textures in architectural plans. 2nd IAPR Workshop on Graphics Recognition.
Abstract: This paper deals with the recognition of symbols and struc- tural textures in architectural plans using string matching techniques. A plan is represented by an attributed graph whose nodes represent characteristic points and whose edges represent segments. Symbols and textures can be seen as a set of regions, i.e. closed loops in the graph, with a particular arrangement. The search for a symbol involves a graph matching between the regions of a model graph and the regions of the graph representing the document. Discriminating a texture means a clus- tering of neighbouring regions of this graph. Both procedures involve a similarity measure between graph regions. A string codification is used to represent the sequence of outlining edges of a region. Thus, the simila- rity between two regions is defined in terms of the string edit distance between their boundary strings. The use of string matching allows the recognition method to work also under presence of distortion.
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Josep Llados, Horst Bunke and Enric Marti. 1997. Finding rotational symmetries by cyclic string matching. PRL, 18(14), 1435–1442.
Abstract: Symmetry is an important shape feature. In this paper, a simple and fast method to detect perfect and distorted rotational symmetries of 2D objects is described. The boundary of a shape is polygonally approximated and represented as a string. Rotational symmetries are found by cyclic string matching between two identical copies of the shape string. The set of minimum cost edit sequences that transform the shape string to a cyclically shifted version of itself define the rotational symmetry and its order. Finally, a modification of the algorithm is proposed to detect reflectional symmetries. Some experimental results are presented to show the reliability of the proposed algorithm
Keywords: Rotational symmetry; Reflectional symmetry; String matching
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Josep Llados, Horst Bunke and Enric Marti. 1997. Using Cyclic String Matching to Find Rotational and Reflectional Symmetries in Shapes. Intelligent Robots: Sensing, Modeling and Planning. World Scientific Press, 164–179.
Abstract: Dagstuhl Workshop
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Josep Llados, Horst Bunke and Enric Marti. 1996. Using cyclic string matching to find rotational and reflectional symmetric shapes. In R.C. Bolles, H.B.H.N., ed. Dagstuhl Seminar on Modelling and Planning for Sensor–based Intelligent Robot Systems. Saarbrucken (Germany)., World Scientific.
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Josep Llados, Horst Bunke and Enric Marti. 1996. Structural Recognition of hand drawn floor plans. VI National Symposium on Pattern Recognition and Image Analysis. Cordoba.
Abstract: A system to recognize hand drawn architectural drawings in a CAD environment has been deve- loped. In this paper we focus on its high level interpretation module. To interpret a floor plan, the system must identify several building elements, whose description is stored in a library of pat- terns, as well as their spatial relationships. We propose a structural approach based on subgraph isomorphism techniques to obtain a high-level interpretation of the document. The vectorized input document and the patterns to be recognized are represented by attributed graphs. Discrete relaxation techniques (AC4 algorithm) have been applied to develop the matching algorithm. The process has been divided in three steps: node labeling, local consistency and global consistency verification. The hand drawn creation causes disturbed line drawings with several accuracy errors, which must be taken into account. Here we have identified them and the AC4 algorithm has been adapted to manage them.
Keywords: Rotational Symmetry; Reflectional Symmetry; String Matching.
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