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Author Hongxing Gao; Marçal Rusiñol; Dimosthenis Karatzas; Apostolos Antonacopoulos; Josep Llados edit   pdf
openurl 
  Title An interactive appearance-based document retrieval system for historical newspapers Type Conference Article
  Year 2013 Publication Proceedings of the International Conference on Computer Vision Theory and Applications Abbreviated Journal  
  Volume Issue Pages 84-87  
  Keywords  
  Abstract In this paper we present a retrieval-based application aimed at assisting a user to semi-automatically segment an incoming flow of historical newspaper images by automatically detecting a particular type of pages based on their appearance. A visual descriptor is used to assess page similarity while a relevance feedback process allow refining the results iteratively. The application is tested on a large dataset of digitised historic newspapers.  
  Address Barcelona; February 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 (down) VISAPP  
  Notes DAG; 600.056; 600.045; 605.203 Approved no  
  Call Number Admin @ si @ GRK2013a Serial 2290  
Permanent link to this record
 

 
Author Christophe Rigaud; Dimosthenis Karatzas; Joost Van de Weijer; Jean-Christophe Burie; Jean-Marc Ogier edit   pdf
openurl 
  Title Automatic text localisation in scanned comic books Type Conference Article
  Year 2013 Publication Proceedings of the International Conference on Computer Vision Theory and Applications Abbreviated Journal  
  Volume Issue Pages 814-819  
  Keywords Text localization; comics; text/graphic separation; complex background; unstructured document  
  Abstract Comic books constitute an important cultural heritage asset in many countries. Digitization combined with subsequent document understanding enable direct content-based search as opposed to metadata only search (e.g. album title or author name). Few studies have been done in this direction. In this work we detail a novel approach for the automatic text localization in scanned comics book pages, an essential step towards a fully automatic comics book understanding. We focus on speech text as it is semantically important and represents the majority of the text present in comics. The approach is compared with existing methods of text localization found in the literature and results are presented.  
  Address Barcelona; February 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 (down) VISAPP  
  Notes DAG; CIC; 600.056 Approved no  
  Call Number Admin @ si @ RKW2013b Serial 2261  
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Author Salvatore Tabbone; Josep Llados edit  openurl
  Title A Propos de la Reconnaissance de Documents Graphiques: Synthese et Perspectives Type Conference Article
  Year 2007 Publication Traitement et Analyse de l’Information: Methodes et Applications Abbreviated Journal  
  Volume Issue Pages 247–258  
  Keywords  
  Abstract  
  Address Hammamet (Tunis)  
  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 (down) TAIMA’07  
  Notes DAG Approved no  
  Call Number DAG @ dag @ TaL2007 Serial 890  
Permanent link to this record
 

 
Author Muhammad Muzzamil Luqman; Jean-Yves Ramel; Josep Llados edit  doi
isbn  openurl
  Title Improving Fuzzy Multilevel Graph Embedding through Feature Selection Technique Type Conference Article
  Year 2012 Publication Structural, Syntactic, and Statistical Pattern Recognition, Joint IAPR International Workshop Abbreviated Journal  
  Volume 7626 Issue Pages 243-253  
  Keywords  
  Abstract Graphs are the most powerful, expressive and convenient data structures but there is a lack of efficient computational tools and algorithms for processing them. The embedding of graphs into numeric vector spaces permits them to access the state-of-the-art computational efficient statistical models and tools. In this paper we take forward our work on explicit graph embedding and present an improvement to our earlier proposed method, named “fuzzy multilevel graph embedding – FMGE”, through feature selection technique. FMGE achieves the embedding of attributed graphs into low dimensional vector spaces by performing a multilevel analysis of graphs and extracting a set of global, structural and elementary level features. Feature selection permits FMGE to select the subset of most discriminating features and to discard the confusing ones for underlying graph dataset. Experimental results for graph classification experimentation on IAM letter, GREC and fingerprint graph databases, show improvement in the performance of FMGE.  
  Address  
  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 978-3-642-34165-6 Medium  
  Area Expedition Conference (down) SSPR&SPR  
  Notes DAG Approved no  
  Call Number Admin @ si @ LRL2012 Serial 2381  
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Author Volkmar Frinken; Alicia Fornes; Josep Llados; Jean-Marc Ogier edit   pdf
doi  isbn
openurl 
  Title Bidirectional Language Model for Handwriting Recognition Type Conference Article
  Year 2012 Publication Structural, Syntactic, and Statistical Pattern Recognition, Joint IAPR International Workshop Abbreviated Journal  
  Volume 7626 Issue Pages 611-619  
  Keywords  
  Abstract In order to improve the results of automatically recognized handwritten text, information about the language is commonly included in the recognition process. A common approach is to represent a text line as a sequence. It is processed in one direction and the language information via n-grams is directly included in the decoding. This approach, however, only uses context on one side to estimate a word’s probability. Therefore, we propose a bidirectional recognition in this paper, using distinct forward and a backward language models. By combining decoding hypotheses from both directions, we achieve a significant increase in recognition accuracy for the off-line writer independent handwriting recognition task. Both language models are of the same type and can be estimated on the same corpus. Hence, the increase in recognition accuracy comes without any additional need for training data or language modeling complexity.  
  Address Japan  
  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 978-3-642-34165-6 Medium  
  Area Expedition Conference (down) SSPR&SPR  
  Notes DAG Approved no  
  Call Number Admin @ si @ FFL2012 Serial 2057  
Permanent link to this record
 

 
Author Klaus Broelemann; Anjan Dutta; Xiaoyi Jiang; Josep Llados edit   pdf
doi  isbn
openurl 
  Title Hierarchical graph representation for symbol spotting in graphical document images Type Conference Article
  Year 2012 Publication Structural, Syntactic, and Statistical Pattern Recognition, Joint IAPR International Workshop Abbreviated Journal  
  Volume 7626 Issue Pages 529-538  
  Keywords  
  Abstract Symbol spotting can be defined as locating given query symbol in a large collection of graphical documents. In this paper we present a hierarchical graph representation for symbols. This representation allows graph matching methods to deal with low-level vectorization errors and, thus, to perform a robust symbol spotting. To show the potential of this approach, we conduct an experiment with the SESYD dataset.  
  Address Miyajima-Itsukushima, Hiroshima  
  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 978-3-642-34165-6 Medium  
  Area Expedition Conference (down) SSPR&SPR  
  Notes DAG Approved no  
  Call Number Admin @ si @ BDJ2012 Serial 2126  
Permanent link to this record
 

 
Author Jaume Gibert; Ernest Valveny; Horst Bunke; Alicia Fornes edit   pdf
doi  isbn
openurl 
  Title On the Correlation of Graph Edit Distance and L1 Distance in the Attribute Statistics Embedding Space Type Conference Article
  Year 2012 Publication Structural, Syntactic, and Statistical Pattern Recognition, Joint IAPR International Workshop Abbreviated Journal  
  Volume 7626 Issue Pages 135-143  
  Keywords  
  Abstract Graph embeddings in vector spaces aim at assigning a pattern vector to every graph so that the problems of graph classification and clustering can be solved by using data processing algorithms originally developed for statistical feature vectors. An important requirement graph features should fulfil is that they reproduce as much as possible the properties among objects in the graph domain. In particular, it is usually desired that distances between pairs of graphs in the graph domain closely resemble those between their corresponding vectorial representations. In this work, we analyse relations between the edit distance in the graph domain and the L1 distance of the attribute statistics based embedding, for which good classification performance has been reported on various datasets. We show that there is actually a high correlation between the two kinds of distances provided that the corresponding parameter values that account for balancing the weight between node and edge based features are properly selected.  
  Address  
  Corporate Author Thesis  
  Publisher Springer-Berlag, Berlin Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN ISBN 978-3-642-34165-6 Medium  
  Area Expedition Conference (down) SSPR&SPR  
  Notes DAG Approved no  
  Call Number Admin @ si @ GVB2012c Serial 2167  
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Author Miquel Ferrer; Ernest Valveny; F. Serratosa; Horst Bunke edit  openurl
  Title Exact Median Graph Computation via Graph Embedding Type Conference Article
  Year 2008 Publication 12th International Workshop on Structural and Syntactic Pattern Recognition Abbreviated Journal  
  Volume 5324 Issue Pages 15–24  
  Keywords  
  Abstract  
  Address Orlando – Florida (USA)  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference (down) SSPR  
  Notes DAG Approved no  
  Call Number DAG @ dag @ FVS2008b Serial 1076  
Permanent link to this record
 

 
Author Hongxing Gao; Marçal Rusiñol; Dimosthenis Karatzas; Josep Llados edit   pdf
doi  openurl
  Title Fast Structural Matching for Document Image Retrieval through Spatial Databases Type Conference Article
  Year 2014 Publication Document Recognition and Retrieval XXI Abbreviated Journal  
  Volume 9021 Issue Pages  
  Keywords Document image retrieval; distance transform; MSER; spatial database  
  Abstract The structure of document images plays a signi cant role in document analysis thus considerable e orts have been made towards extracting and understanding document structure, usually in the form of layout analysis approaches. In this paper, we rst employ Distance Transform based MSER (DTMSER) to eciently extract stable document structural elements in terms of a dendrogram of key-regions. Then a fast structural matching method is proposed to query the structure of document (dendrogram) based on a spatial database which facilitates the formulation of advanced spatial queries. The experiments demonstrate a signi cant improvement in a document retrieval scenario when compared to the use of typical Bag of Words (BoW) and pyramidal BoW descriptors.  
  Address Amsterdam; September 2014  
  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 (down) SPIE-DRR  
  Notes DAG; 600.056; 600.061; 600.077 Approved no  
  Call Number Admin @ si @ GRK2014a Serial 2496  
Permanent link to this record
 

 
Author Partha Pratim Roy; Umapada Pal; Josep Llados edit  url
doi  openurl
  Title Seal Object Detection in Document Images using GHT of Local Component Shapes Type Conference Article
  Year 2010 Publication 10th ACM Symposium On Applied Computing Abbreviated Journal  
  Volume Issue Pages 23–27  
  Keywords  
  Abstract Due to noise, overlapped text/signature and multi-oriented nature, seal (stamp) object detection involves a difficult challenge. This paper deals with automatic detection of seal from documents with cluttered background. Here, a seal object is characterized by scale and rotation invariant spatial feature descriptors (distance and angular position) computed from recognition result of individual connected components (characters). Recognition of multi-scale and multi-oriented component is done using Support Vector Machine classifier. Generalized Hough Transform (GHT) is used to detect the seal and a voting is casted for finding possible location of the seal object in a document based on these spatial feature descriptor of components pairs. The peak of votes in GHT accumulator validates the hypothesis to locate the seal object in a document. Experimental results show that, the method is efficient to locate seal instance of arbitrary shape and orientation in documents.  
  Address Sierre, Switzerland  
  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 (down) SAC  
  Notes DAG Approved no  
  Call Number DAG @ dag @ RPL2010a Serial 1291  
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