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Author Pau Riba; Josep Llados; Alicia Fornes; Anjan Dutta edit   pdf
url  doi
isbn  openurl
  Title Large-scale Graph Indexing using Binary Embeddings of Node Contexts Type Conference Article
  Year 2015 Publication 10th IAPR-TC15 Workshop on Graph-based Representations in Pattern Recognition Abbreviated Journal  
  Volume 9069 Issue Pages 208-217  
  Keywords Graph matching; Graph indexing; Application in document analysis; Word spotting; Binary embedding  
  Abstract Graph-based representations are experiencing a growing usage in visual recognition and retrieval due to their representational power in front of classical appearance-based representations in terms of feature vectors. Retrieving a query graph from a large dataset of graphs has the drawback of the high computational complexity required to compare the query and the target graphs. The most important property for a large-scale retrieval is the search time complexity to be sub-linear in the number of database examples. In this paper we propose a fast indexation formalism for graph retrieval. A binary embedding is defined as hashing keys for graph nodes. Given a database of labeled graphs, graph nodes are complemented with vectors of attributes representing their local context. Hence, each attribute counts the length of a walk of order k originated in a vertex with label l. Each attribute vector is converted to a binary code applying a binary-valued hash function. Therefore, graph retrieval is formulated in terms of finding target graphs in the database whose nodes have a small Hamming distance from the query nodes, easily computed with bitwise logical operators. As an application example, we validate the performance of the proposed methods in a handwritten word spotting scenario in images of historical documents.  
  Address Beijing; China; May 2015  
  Corporate Author Thesis  
  Publisher (up) Springer International Publishing Place of Publication Editor C.-L.Liu; B.Luo; W.G.Kropatsch; J.Cheng  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN 0302-9743 ISBN 978-3-319-18223-0 Medium  
  Area Expedition Conference GbRPR  
  Notes DAG; 600.061; 602.006; 600.077 Approved no  
  Call Number Admin @ si @ RLF2015a Serial 2618  
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Author Suman Ghosh; Ernest Valveny edit   pdf
doi  isbn
openurl 
  Title A Sliding Window Framework for Word Spotting Based on Word Attributes Type Conference Article
  Year 2015 Publication Pattern Recognition and Image Analysis, Proceedings of 7th Iberian Conference , ibPRIA 2015 Abbreviated Journal  
  Volume 9117 Issue Pages 652-661  
  Keywords Word spotting; Sliding window; Word attributes  
  Abstract In this paper we propose a segmentation-free approach to word spotting. Word images are first encoded into feature vectors using Fisher Vector. Then, these feature vectors are used together with pyramidal histogram of characters labels (PHOC) to learn SVM-based attribute models. Documents are represented by these PHOC based word attributes. To efficiently compute the word attributes over a sliding window, we propose to use an integral image representation of the document using a simplified version of the attribute model. Finally we re-rank the top word candidates using the more discriminative full version of the word attributes. We show state-of-the-art results for segmentation-free query-by-example word spotting in single-writer and multi-writer standard datasets.  
  Address Santiago de Compostela; June 2015  
  Corporate Author Thesis  
  Publisher (up) Springer International Publishing 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 978-3-319-19389-2 Medium  
  Area Expedition Conference IbPRIA  
  Notes DAG; 600.077 Approved no  
  Call Number Admin @ si @ GhV2015b Serial 2716  
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Author Pau Riba; Josep Llados; Alicia Fornes edit   pdf
doi  openurl
  Title Error-tolerant coarse-to-fine matching model for hierarchical graphs Type Conference Article
  Year 2017 Publication 11th IAPR-TC-15 International Workshop on Graph-Based Representations in Pattern Recognition Abbreviated Journal  
  Volume 10310 Issue Pages 107-117  
  Keywords Graph matching; Hierarchical graph; Graph-based representation; Coarse-to-fine matching  
  Abstract Graph-based representations are effective tools to capture structural information from visual elements. However, retrieving a query graph from a large database of graphs implies a high computational complexity. Moreover, these representations are very sensitive to noise or small changes. In this work, a novel hierarchical graph representation is designed. Using graph clustering techniques adapted from graph-based social media analysis, we propose to generate a hierarchy able to deal with different levels of abstraction while keeping information about the topology. For the proposed representations, a coarse-to-fine matching method is defined. These approaches are validated using real scenarios such as classification of colour images and handwritten word spotting.  
  Address Anacapri; Italy; May 2017  
  Corporate Author Thesis  
  Publisher (up) Springer International Publishing Place of Publication Editor Pasquale Foggia; Cheng-Lin Liu; Mario Vento  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference GbRPR  
  Notes DAG; 600.097; 601.302; 600.121 Approved no  
  Call Number Admin @ si @ RLF2017a Serial 2951  
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Author Pau Riba; Alicia Fornes; Josep Llados edit  isbn
openurl 
  Title Towards the Alignment of Handwritten Music Scores Type Conference Article
  Year 2015 Publication 11th IAPR International Workshop on Graphics Recognition Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract It is very common to find different versions of the same music work in archives of Opera Theaters. These differences correspond to modifications and annotations from the musicians. From the musicologist point of view, these variations are very interesting and deserve study. This paper explores the alignment of music scores as a tool for automatically detecting the passages that contain such differences. Given the difficulties in the recognition of handwritten music scores, our goal is to align the music scores and at the same time, avoid the recognition of music elements as much as possible. After removing the staff lines, braces and ties, the bar lines are detected. Then, the bar units are described as a whole using the Blurred Shape Model. The bar units alignment is performed by using Dynamic Time Warping. The analysis of the alignment path is used to detect the variations in the music scores. The method has been evaluated on a subset of the CVC-MUSCIMA dataset, showing encouraging results.  
  Address Nancy; France; August 2015  
  Corporate Author Thesis  
  Publisher (up) Springer International Publishing Place of Publication Editor Bart Lamiroy; Rafael Dueire Lins  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN ISBN 978-3-319-52158-9 Medium  
  Area Expedition Conference GREC  
  Notes DAG Approved no  
  Call Number Admin @ si @ Serial 2874  
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Author Juan Ignacio Toledo; Sebastian Sudholt; Alicia Fornes; Jordi Cucurull; A. Fink; Josep Llados edit   pdf
url  isbn
openurl 
  Title Handwritten Word Image Categorization with Convolutional Neural Networks and Spatial Pyramid Pooling Type Conference Article
  Year 2016 Publication Joint IAPR International Workshops on Statistical Techniques in Pattern Recognition (SPR) and Structural and Syntactic Pattern Recognition (SSPR) Abbreviated Journal  
  Volume 10029 Issue Pages 543-552  
  Keywords Document image analysis; Word image categorization; Convolutional neural networks; Named entity detection  
  Abstract The extraction of relevant information from historical document collections is one of the key steps in order to make these documents available for access and searches. The usual approach combines transcription and grammars in order to extract semantically meaningful entities. In this paper, we describe a new method to obtain word categories directly from non-preprocessed handwritten word images. The method can be used to directly extract information, being an alternative to the transcription. Thus it can be used as a first step in any kind of syntactical analysis. The approach is based on Convolutional Neural Networks with a Spatial Pyramid Pooling layer to deal with the different shapes of the input images. We performed the experiments on a historical marriage record dataset, obtaining promising results.  
  Address Merida; Mexico; December 2016  
  Corporate Author Thesis  
  Publisher (up) Springer International Publishing Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN ISBN 978-3-319-49054-0 Medium  
  Area Expedition Conference S+SSPR  
  Notes DAG; 600.097; 602.006 Approved no  
  Call Number Admin @ si @ TSF2016 Serial 2877  
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Author Alicia Fornes; Bart Lamiroy edit  url
isbn  openurl
  Title Graphics Recognition, Current Trends and Evolutions Type Book Whole
  Year 2018 Publication Graphics Recognition, Current Trends and Evolutions Abbreviated Journal  
  Volume 11009 Issue Pages  
  Keywords  
  Abstract This book constitutes the thoroughly refereed post-conference proceedings of the 12th International Workshop on Graphics Recognition, GREC 2017, held in Kyoto, Japan, in November 2017.
The 10 revised full papers presented were carefully reviewed and selected from 14 initial submissions. They contain both classical and emerging topics of graphics rcognition, namely analysis and detection of diagrams, search and classification, optical music recognition, interpretation of engineering drawings and maps.
 
  Address  
  Corporate Author Thesis  
  Publisher (up) Springer International Publishing Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN ISBN 978-3-030-02283-9 Medium  
  Area Expedition Conference  
  Notes DAG; 600.121 Approved no  
  Call Number Admin @ si @ FoL2018 Serial 3171  
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Author Agnes Borras; Josep Llados edit   pdf
url  doi
openurl 
  Title Object Image Retrieval by Shape Content in Complex Scenes Using Geometric Constraints Type Book Chapter
  Year 2005 Publication Pattern Recognition And Image Analysis Abbreviated Journal LNCS  
  Volume 3522 Issue Pages 325–332  
  Keywords  
  Abstract This paper presents an image retrieval system based on 2D shape information. Query shape objects and database images are repre- sented by polygonal approximations of their contours. Afterwards they are encoded, using geometric features, in terms of predefined structures. Shapes are then located in database images by a voting procedure on the spatial domain. Then an alignment matching provides a probability value to rank de database image in the retrieval result. The method al- lows to detect a query object in database images even when they contain complex scenes. Also the shape matching tolerates partial occlusions and affine transformations as translation, rotation or scaling.  
  Address Estoril (Portugal)  
  Corporate Author Thesis  
  Publisher (up) Springer Link 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; Approved no  
  Call Number DAG @ dag @ BoL2005; IAM @ iam @ BoL2005 Serial 556  
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Author Anton Cervantes; Gemma Sanchez; Josep Llados; Agnes Borras; Ana Rodriguez edit   pdf
url  openurl
  Title Biometric Recognition Based on Line Shape Descriptors Type Book Chapter
  Year 2006 Publication Lecture Notes in Computer Science Abbreviated Journal  
  Volume 3926 Issue Pages 346–357,  
  Keywords  
  Abstract Abstract. In this paper we propose biometric descriptors inspired by shape signatures traditionally used in graphics recognition approaches. In particular several methods based on line shape descriptors used to iden- tify newborns from the biometric information of the ears are developed. The process steps are the following: image acquisition, ear segmentation, ear normalization, feature extraction and identification. Several shape signatures are defined from contour images. These are formulated in terms of zoning and contour crossings descriptors. Experimental results are presented to demonstrate the effectiveness of the used techniques.  
  Address  
  Corporate Author Thesis  
  Publisher (up) Springer Link 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 Approved no  
  Call Number DAG @ dag @ CSL2006 Serial 685  
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Author Josep Llados; Gemma Sanchez; Enric Marti edit   pdf
doi  openurl
  Title A string based method to recognize symbols and structural textures in architectural plans Type Book Chapter
  Year 1998 Publication Graphics Recognition Algorithms and Systems Second International Workshop, GREC' 97 Nancy, France, August 22–23, 1997 Selected Papers Abbreviated Journal LNCS  
  Volume 1389 Issue 1998 Pages 91-103  
  Keywords  
  Abstract This paper deals with the recognition of symbols and structural 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 clustering 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 similarity 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.  
  Address  
  Corporate Author Thesis  
  Publisher (up) Springer Link Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title LNCS Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes DAG; IAM Approved no  
  Call Number IAM @ iam @ SLE1998 Serial 1573  
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Author Jean-Marc Ogier; Wenyin Liu; Josep Llados (eds) edit  isbn
openurl 
  Title Graphics Recognition: Achievements, Challenges, and Evolution Type Book Whole
  Year 2010 Publication 8th International Workshop GREC 2009. Abbreviated Journal  
  Volume 6020 Issue Pages  
  Keywords  
  Abstract  
  Address La Rochelle  
  Corporate Author Thesis  
  Publisher (up) Springer Link Place of Publication Editor Jean-Marc Ogier; Wenyin Liu; Josep Llados  
  Language Summary Language Original Title  
  Series Editor Series Title Lecture Notes in Computer Science Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN ISBN 978-3-642-13727-3 Medium  
  Area Expedition Conference GREC  
  Notes DAG Approved no  
  Call Number Admin @ si @ OLL2010 Serial 1976  
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