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Author Gemma Sanchez; Josep Llados; Enric Marti edit  openurl
  Title Segmentation and analysis of linial texture in plans Type Conference Article
  Year 1997 Publication Actes de la conférence Artificielle et Complexité. Abbreviated Journal  
  Volume Issue Pages (up)  
  Keywords Structural Texture, Voronoi, Hierarchical Clustering, String Matching.  
  Abstract The problem of texture segmentation and interpretation is one of the main concerns in the field of document analysis. Graphical documents often contain areas characterized by a structural texture whose recognition allows both the document understanding, and its storage in a more compact way. In this work, we focus on structural linial textures of regular repetition contained in plan documents. Starting from an atributed graph which represents the vectorized input image, we develop a method to segment textured areas and recognize their placement rules. We wish to emphasize that the searched textures do not follow a predefined pattern. Minimal closed loops of the input graph are computed, and then hierarchically clustered. In this hierarchical clustering, a distance function between two closed loops is defined in terms of their areas difference and boundary resemblance computed by a string matching procedure. Finally it is noted that, when the texture consists of isolated primitive elements, the same method can be used after computing a Voronoi Tesselation of the input graph.  
  Address Paris, France  
  Corporate Author Thesis  
  Publisher Place of Publication Paris Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference AERFAI  
  Notes DAG;IAM; Approved no  
  Call Number IAM @ iam @ SLM1997 Serial 1649  
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Author Ernest Valveny; Enric Marti edit   pdf
url  doi
openurl 
  Title Application of deformable template matching to symbol recognition in hand-written architectural draw Type Conference Article
  Year 1999 Publication Proceedings of the Fifth International Conference on Abbreviated Journal  
  Volume Issue Pages (up)  
  Keywords  
  Abstract We propose to use deformable template matching as a new approach to recognize characters and lineal symbols in hand-written line drawings, instead of traditional methods based on vectorization and feature extraction. Bayesian formulation of the deformable template matching allows combining fidelity to the ideal shape of the symbol with maximum flexibility to get the best fit to the input image. Lineal nature of symbols can be exploited to define a suitable representation of models and the set of deformations to be applied to them. Matching, however, is done over the original binary image to avoid losing relevant features during vectorization. We have applied this method to hand-written architectural drawings and experimental results demonstrate that symbols with high distortions from ideal shape can be accurately identified.  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Bangalore (India) Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes DAG;IAM; Approved no  
  Call Number IAM @ iam @ VAM1999a Serial 1657  
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Author Ernest Valveny; Enric Marti edit  openurl
  Title Recognition of lineal symbols in hand-written drawings using deformable template matching Type Conference Article
  Year 1999 Publication Proceedings of the VIII Symposium Nacional de Reconocimiento de Formas y Análisis de Imágenes Abbreviated Journal  
  Volume Issue Pages (up)  
  Keywords  
  Abstract  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes DAG;IAM; Approved no  
  Call Number IAM @ iam @ VAM1999 Serial 1658  
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Author Klaus Broelemann; Anjan Dutta; Xiaoyi Jiang; Josep Llados edit   pdf
openurl 
  Title Plausibility-Graphs for Symbol Spotting in Graphical Documents Type Conference Article
  Year 2013 Publication 10th IAPR International Workshop on Graphics Recognition Abbreviated Journal  
  Volume Issue Pages (up)  
  Keywords  
  Abstract Graph representation of graphical documents often suffers from noise viz. spurious nodes and spurios edges of graph and their discontinuity etc. In general these errors occur during the low-level image processing viz. binarization, skeletonization, vectorization etc. Hierarchical graph representation is a nice and efficient way to solve this kind of problem by hierarchically merging node-node and node-edge depending on the distance.
But the creation of hierarchical graph representing the graphical information often uses hard thresholds on the distance to create the hierarchical nodes (next state) of the lower nodes (or states) of a graph. As a result the representation often loses useful information. This paper introduces plausibilities to the nodes of hierarchical graph as a function of distance and proposes a modified algorithm for matching subgraphs of the hierarchical
graphs. The plausibility-annotated nodes help to improve the performance of the matching algorithm on two hierarchical structures. To show the potential of this approach, we conduct an experiment with the SESYD dataset.
 
  Address Bethlehem; PA; USA; August 2013  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference GREC  
  Notes DAG; 600.045; 600.056; 600.061; 601.152 Approved no  
  Call Number Admin @ si @ BDJ2013 Serial 2360  
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Author Anjan Dutta; Josep Llados; Horst Bunke; Umapada Pal edit   pdf
openurl 
  Title A Product graph based method for dual subgraph matching applied to symbol spotting Type Conference Article
  Year 2013 Publication 10th IAPR International Workshop on Graphics Recognition Abbreviated Journal  
  Volume Issue Pages (up)  
  Keywords  
  Abstract Product graph has been shown to be an efficient way for matching subgraphs. This paper reports the extension of the product graph methodology for subgraph matching applied to symbol spotting in graphical documents. This paper focuses on the two major limitations of the previous version of product graph: (1) Spurious nodes and edges in the graph representation and (2) Inefficient node and edge attributes. To deal with noisy information of vectorized graphical documents, we consider a dual graph representation on the original graph representing the graphical information and the product graph is computed between the dual graphs of the query graphs and the input graph.
The dual graph with redundant edges is helpful for efficient and tolerating encoding of the structural information of the graphical documents. The adjacency matrix of the product graph locates similar path information of two graphs and exponentiating the adjacency matrix finds similar paths of greater lengths. Nodes joining similar paths between two graphs are found by combining different exponentials of adjacency matrices. An experimental investigation reveals that the recall obtained by this approach is quite encouraging.
 
  Address Bethlehem; PA; USA; August 2013  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference GREC  
  Notes DAG Approved no  
  Call Number Admin @ si @ DLB2013b Serial 2359  
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Author Lluis Pere de las Heras; Joan Mas; Gemma Sanchez; Ernest Valveny edit  openurl
  Title Descriptor-based Svm Wall Detector Type Conference Article
  Year 2011 Publication 9th International Workshop on Graphic Recognition Abbreviated Journal  
  Volume Issue Pages (up)  
  Keywords  
  Abstract Architectural floorplans exhibit a large variability in notation. Therefore, segmenting and identifying the elements of any kind of plan becomes a challenging task for approaches based on grouping structural primitives obtained by vectorization. Recently, a patch-based segmentation method working at pixel level and relying on the construction of a visual vocabulary has been proposed showing its adaptability to different notations by automatically learning the visual appearance of the elements in each different notation. In this paper we describe an evolution of this new approach in two directions: firstly we evaluate different features to obtain the description of every patch. Secondly, we train an SVM classifier to obtain the category of every patch instead of constructing a visual vocabulary. These modifications of the method have been tested for wall detection on two datasets of architectural floorplans with different notations and compared with the results obtained with the original approach.  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference GREC  
  Notes DAG Approved no  
  Call Number Admin @ si @ HMS2011b Serial 1819  
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Author Marçal Rusiñol; V. Poulain d'Andecy; Dimosthenis Karatzas; Josep Llados edit  openurl
  Title Classification of Administrative Document Images by Logo Identification Type Conference Article
  Year 2011 Publication In proceedings of 9th IAPR Workshop on Graphic Recognition Abbreviated Journal  
  Volume Issue Pages (up)  
  Keywords  
  Abstract This paper is focused on the categorization of administrative document images (such as invoices) based on the recognition of the supplier's graphical logo. Two different methods are proposed, the first one uses a bag-of-visual-words model whereas the second one tries to locate logo images described by the blurred shape model descriptor within documents by a sliding-window technique. Preliminar results are reported with a dataset of real administrative documents.  
  Address Seoul, Corea  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference GREC  
  Notes DAG Approved no  
  Call Number Admin @ si @ RPK2011 Serial 1821  
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Author Anjan Dutta; Josep Llados; Umapada Pal edit  doi
isbn  openurl
  Title Bag-of-GraphPaths Descriptors for Symbol Recognition and Spotting in Line Drawings Type Conference Article
  Year 2011 Publication In proceedings of 9th IAPR Workshop on Graphic Recognition Abbreviated Journal  
  Volume Issue Pages (up)  
  Keywords  
  Abstract Graphical symbol recognition and spotting recently have become an important research activity. In this work we present a descriptor for symbols, especially for line drawings. The descriptor is based on the graph representation of graphical objects. We construct graphs from the vectorized information of the binarized images, where the critical points detected by the vectorization algorithm are considered as nodes and the lines joining them are considered as edges. Graph paths between two nodes in a graph are the finite sequences of nodes following the order from the starting to the final node. The occurrences of different graph paths in a given graph is an important feature, as they capture the geometrical and structural attributes of a graph. So the graph representing a symbol can efficiently be represent by the occurrences of its different paths. Their occurrences in a symbol can be obtained in terms of a histogram counting the number of some fixed prototype paths, we call the histogram as the Bag-of-GraphPaths (BOGP). These BOGP histograms are used as a descriptor to measure the distance among the symbols in vector space. We use the descriptor for three applications, they are: (1) classification of the graphical symbols, (2) spotting of the architectural symbols on floorplans, (3) classification of the historical handwritten words.  
  Address Seoul, Korea  
  Corporate Author Thesis  
  Publisher Springer Berlin Heidelberg Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN 0302-9743 ISBN 978-3-642-36823-3 Medium  
  Area Expedition Conference GREC  
  Notes DAG Approved no  
  Call Number Admin @ si @ DLP2011c Serial 1825  
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Author V.C.Kieu; Alicia Fornes; M. Visani; N.Journet ; Anjan Dutta edit   pdf
openurl 
  Title The ICDAR/GREC 2013 Music Scores Competition on Staff Removal Type Conference Article
  Year 2013 Publication 10th IAPR International Workshop on Graphics Recognition Abbreviated Journal  
  Volume Issue Pages (up)  
  Keywords Competition; Music scores; Staff Removal  
  Abstract The first competition on music scores that was organized at ICDAR and GREC in 2011 awoke the interest of researchers, who participated both at staff removal and writer identification tasks. In this second edition, we propose a staff removal competition where we simulate old music scores. Thus, we have created a new set of images, which contain noise and 3D distortions. This paper describes the distortion methods, metrics, the participant’s methods and the obtained results.  
  Address Bethlehem; PA; USA; August 2013  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference GREC  
  Notes DAG; 600.045; 600.061 Approved no  
  Call Number Admin @ si @ KFV2013 Serial 2337  
Permanent link to this record
 

 
Author Marçal Rusiñol; V. Poulain d'Andecy; Dimosthenis Karatzas; Josep Llados edit   pdf
openurl 
  Title Classification of Administrative Document Images by Logo Identification Type Conference Article
  Year 2013 Publication 10th IAPR International Workshop on Graphics Recognition Abbreviated Journal  
  Volume Issue Pages (up)  
  Keywords  
  Abstract This paper is focused on the categorization of administrative document images (such as invoices) based on the recognition of the supplier's graphical logo. Two different methods are proposed, the first one uses a bag-of-visual-words model whereas the second one tries to locate logo images described by the blurred shape model descriptor within documents by a sliding-window technique. Preliminar results are reported with a dataset of real administrative documents.  
  Address Bethlehem; PA; USA; August 2013  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference GREC  
  Notes DAG; 600.056; 600.045; 605.203 Approved no  
  Call Number Admin @ si @ Serial 2348  
Permanent link to this record
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