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Author Miquel Ferrer; Dimosthenis Karatzas; Ernest Valveny; Horst Bunke edit  doi
isbn  openurl
  Title A Recursive Embedding Approach to Median Graph Computation Type Conference Article
  Year 2009 Publication 7th IAPR – TC–15 Workshop on Graph–Based Representations in Pattern Recognition Abbreviated Journal  
  Volume 5534 Issue Pages 113–123  
  Keywords  
  Abstract The median graph has been shown to be a good choice to infer a representative of a set of graphs. It has been successfully applied to graph-based classification and clustering. Nevertheless, its computation is extremely complex. Several approaches have been presented up to now based on different strategies. In this paper we present a new approximate recursive algorithm for median graph computation based on graph embedding into vector spaces. Preliminary experiments on three databases show that this new approach is able to obtain better medians than the previous existing approaches.  
  Address Venice, Italy  
  Corporate Author Thesis  
  Publisher Springer Berlin Heidelberg Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title (up) LNCS  
  Series Volume Series Issue Edition  
  ISSN 0302-9743 ISBN 978-3-642-02123-7 Medium  
  Area Expedition Conference GBR  
  Notes DAG Approved no  
  Call Number DAG @ dag @ FKV2009 Serial 1173  
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Author Miquel Ferrer; Ernest Valveny; F. Serratosa edit  doi
isbn  openurl
  Title Median Graph Computation by means of a Genetic Approach Based on Minimum Common Supergraph and Maximum Common Subraph Type Conference Article
  Year 2009 Publication 4th Iberian Conference on Pattern Recognition and Image Analysis Abbreviated Journal  
  Volume 5524 Issue Pages 346–353  
  Keywords  
  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 a new genetic algorithm for the median graph computation. 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, show that we obtain good approximations of the median graph. Finally, we use the median graph in a real nearest neighbour classification showing that it leaves the box of the only-theoretical concepts and demonstrating, from a practical point of view, that can be a useful tool to represent a set of graphs.  
  Address Póvoa de Varzim, Portugal  
  Corporate Author Thesis  
  Publisher Springer Berlin Heidelberg Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title (up) LNCS  
  Series Volume Series Issue Edition  
  ISSN 0302-9743 ISBN 978-3-642-02171-8 Medium  
  Area Expedition Conference IbPRIA  
  Notes DAG Approved no  
  Call Number DAG @ dag @ FVS2009c Serial 1174  
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Author Albert Gordo; Ernest Valveny edit  doi
isbn  openurl
  Title The diagonal split: A pre-segmentation step for page layout analysis & classification Type Conference Article
  Year 2009 Publication 4th Iberian Conference on Pattern Recognition and Image Analysis Abbreviated Journal  
  Volume 5524 Issue Pages 290–297  
  Keywords  
  Abstract Document classification is an important task in all the processes related to document storage and retrieval. In the case of complex documents, structural features are needed to achieve a correct classification. Unfortunately, physical layout analysis is error prone. In this paper we present a pre-segmentation step based on a divide & conquer strategy that can be used to improve the page segmentation results, independently of the segmentation algorithm used. This pre-segmentation step is evaluated in classification and retrieval using the selective CRLA algorithm for layout segmentation together with a clustering based on the voronoi area diagram, and tested on two different databases, MARG and Girona Archives.  
  Address Póvoa de Varzim, Portugal  
  Corporate Author Thesis  
  Publisher Springer Berlin Heidelberg Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title (up) LNCS  
  Series Volume Series Issue Edition  
  ISSN 0302-9743 ISBN 978-3-642-02171-8 Medium  
  Area Expedition Conference IbPRIA  
  Notes DAG Approved no  
  Call Number DAG @ dag @ Gov2009b Serial 1176  
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Author Sergio Escalera; Alicia Fornes; Oriol Pujol; Petia Radeva edit  doi
isbn  openurl
  Title Multi-class Binary Symbol Classification with Circular Blurred Shape Models Type Conference Article
  Year 2009 Publication 15th International Conference on Image Analysis and Processing Abbreviated Journal  
  Volume 5716 Issue Pages 1005–1014  
  Keywords  
  Abstract Multi-class binary symbol classification requires the use of rich descriptors and robust classifiers. Shape representation is a difficult task because of several symbol distortions, such as occlusions, elastic deformations, gaps or noise. In this paper, we present the Circular Blurred Shape Model descriptor. This descriptor encodes the arrangement information of object parts in a correlogram structure. A prior blurring degree defines the level of distortion allowed to the symbol. Moreover, we learn the new feature space using a set of Adaboost classifiers, which are combined in the Error-Correcting Output Codes framework to deal with the multi-class categorization problem. The presented work has been validated over different multi-class data sets, and compared to the state-of-the-art descriptors, showing significant performance improvements.  
  Address Salerno, Italy  
  Corporate Author Thesis  
  Publisher Springer Berlin Heidelberg Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title (up) LNCS  
  Series Volume Series Issue Edition  
  ISSN 0302-9743 ISBN 978-3-642-04145-7 Medium  
  Area Expedition Conference ICIAP  
  Notes MILAB;HuPBA;DAG Approved no  
  Call Number BCNPCL @ bcnpcl @ EFP2009c Serial 1186  
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Author Miquel Ferrer; Ernest Valveny; F. Serratosa; I. Bardaji; Horst Bunke edit  doi
isbn  openurl
  Title Graph-based k-means clustering: A comparison of the set versus the generalized median graph Type Conference Article
  Year 2009 Publication 13th International Conference on Computer Analysis of Images and Patterns Abbreviated Journal  
  Volume 5702 Issue Pages 342–350  
  Keywords  
  Abstract In this paper we propose the application of the generalized median graph in a graph-based k-means clustering algorithm. In the graph-based k-means algorithm, the centers of the clusters have been traditionally represented using the set median graph. We propose an approximate method for the generalized median graph computation that allows to use it to represent the centers of the clusters. Experiments on three databases show that using the generalized median graph as the clusters representative yields better results than the set median graph.  
  Address Münster, Germany  
  Corporate Author Thesis  
  Publisher Springer Berlin Heidelberg Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title (up) LNCS  
  Series Volume Series Issue Edition  
  ISSN 0302-9743 ISBN 978-3-642-03766-5 Medium  
  Area Expedition Conference CAIP  
  Notes DAG Approved no  
  Call Number DAG @ dag @ FVS2009d Serial 1219  
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Author Jaume Gibert; Ernest Valveny edit  doi
isbn  openurl
  Title Graph Embedding based on Nodes Attributes Representatives and a Graph of Words Representation. Type Conference Article
  Year 2010 Publication 13th International worshop on structural and syntactic pattern recognition and 8th international worshop on statistical pattern recognition Abbreviated Journal  
  Volume 6218 Issue Pages 223–232  
  Keywords  
  Abstract Although graph embedding has recently been used to extend statistical pattern recognition techniques to the graph domain, some existing embeddings are usually computationally expensive as they rely on classical graph-based operations. In this paper we present a new way to embed graphs into vector spaces by first encapsulating the information stored in the original graph under another graph representation by clustering the attributes of the graphs to be processed. This new representation makes the association of graphs to vectors an easy step by just arranging both node attributes and the adjacency matrix in the form of vectors. To test our method, we use two different databases of graphs whose nodes attributes are of different nature. A comparison with a reference method permits to show that this new embedding is better in terms of classification rates, while being much more faster.  
  Address  
  Corporate Author Thesis  
  Publisher Springer Berlin Heidelberg Place of Publication Editor In E.R. Hancock, R.C. Wilson, T. Windeatt, I. Ulusoy and F. Escolano,  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title (up) LNCS  
  Series Volume Series Issue Edition  
  ISSN 0302-9743 ISBN 978-3-642-14979-5 Medium  
  Area Expedition Conference S+SSPR  
  Notes DAG Approved no  
  Call Number DAG @ dag @ GiV2010 Serial 1416  
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Author Salim Jouili; Salvatore Tabbone; Ernest Valveny edit  openurl
  Title Comparing Graph Similarity Measures for Graphical Recognition. Type Conference Article
  Year 2009 Publication 8th IAPR International Workshop on Graphics Recognition Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract In this paper we evaluate four graph distance measures. The analysis is performed for document retrieval tasks. For this aim, different kind of documents are used including line drawings (symbols), ancient documents (ornamental letters), shapes and trademark-logos. The experimental results show that the performance of each graph distance measure depends on the kind of data and the graph representation technique.  
  Address La Rochelle; France; July 2009  
  Corporate Author Thesis  
  Publisher Springer Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title (up) LNCS  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference GREC  
  Notes DAG Approved no  
  Call Number DAG @ dag @ JTV2009 Serial 1442  
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Author Muhammad Muzzamil Luqman; Josep Llados; Jean-Yves Ramel; Thierry Brouard edit  doi
isbn  openurl
  Title A Fuzzy-Interval Based Approach For Explicit Graph Embedding, Recognizing Patterns in Signals, Speech, Images and Video Type Conference Article
  Year 2010 Publication 20th International Conference on Pattern Recognition Abbreviated Journal  
  Volume 6388 Issue Pages 93–98  
  Keywords  
  Abstract We present a new method for explicit graph embedding. Our algorithm extracts a feature vector for an undirected attributed graph. The proposed feature vector encodes details about the number of nodes, number of edges, node degrees, the attributes of nodes and the attributes of edges in the graph. The first two features are for the number of nodes and the number of edges. These are followed by w features for node degrees, m features for k node attributes and n features for l edge attributes — which represent the distribution of node degrees, node attribute values and edge attribute values, and are obtained by defining (in an unsupervised fashion), fuzzy-intervals over the list of node degrees, node attributes and edge attributes. Experimental results are provided for sample data of ICPR2010 contest GEPR.  
  Address  
  Corporate Author Thesis  
  Publisher Springer, Heidelberg Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title (up) LNCS  
  Series Volume Series Issue Edition  
  ISSN 0302-9743 ISBN 978-3-642-17710-1 Medium  
  Area Expedition Conference ICPR  
  Notes DAG Approved no  
  Call Number DAG @ dag @ LLR2010 Serial 1459  
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Author Jaume Gibert; Ernest Valveny; Horst Bunke edit  url
doi  isbn
openurl 
  Title Graph of Words Embedding for Molecular Structure-Activity Relationship Analysis Type Conference Article
  Year 2010 Publication 15th Iberoamerican Congress on Pattern Recognition Abbreviated Journal  
  Volume 6419 Issue Pages 30–37  
  Keywords  
  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.  
  Address Sao Paulo, Brazil  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title (up) LNCS  
  Series Volume Series Issue Edition  
  ISSN 0302-9743 ISBN 978-3-642-16686-0 Medium  
  Area Expedition Conference CIARP  
  Notes DAG Approved no  
  Call Number DAG @ dag @ GVB2010 Serial 1462  
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Author Josep Llados; Ernest Valveny; Gemma Sanchez; Enric Marti edit   pdf
url  doi
isbn  openurl
  Title Symbol recognition: current advances and perspectives Type Book Chapter
  Year 2002 Publication Graphics Recognition Algorithms And Applications Abbreviated Journal LNCS  
  Volume 2390 Issue Pages 104-128  
  Keywords  
  Abstract The recognition of symbols in graphic documents is an intensive research activity in the community of pattern recognition and document analysis. A key issue in the interpretation of maps, engineering drawings, diagrams, etc. is the recognition of domain dependent symbols according to a symbol database. In this work we first review the most outstanding symbol recognition methods from two different points of view: application domains and pattern recognition methods. In the second part of the paper, open and unaddressed problems involved in symbol recognition are described, analyzing their current state of art and discussing future research challenges. Thus, issues such as symbol representation, matching, segmentation, learning, scalability of recognition methods and performance evaluation are addressed in this work. Finally, we discuss the perspectives of symbol recognition concerning to new paradigms such as user interfaces in handheld computers or document database and WWW indexing by graphical content.  
  Address London, UK  
  Corporate Author Thesis  
  Publisher Springer-Verlag Place of Publication Editor Dorothea Blostein and Young- Bin Kwon  
  Language Summary Language Original Title  
  Series Editor Series Title Lecture Notes in Computer Science Abbreviated Series Title (up) LNCS  
  Series Volume Series Issue Edition  
  ISSN ISBN 3-540-44066-6 Medium  
  Area Expedition Conference GREC  
  Notes DAG; IAM; Approved no  
  Call Number IAM @ iam @ LVS2002 Serial 1572  
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