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Author Albert Gordo; Ernest Valveny edit  doi
isbn  openurl
  Title A rotation invariant page layout descriptor for document classification and retrieval Type Conference Article
  Year 2009 Publication 10th International Conference on Document Analysis and Recognition Abbreviated Journal  
  Volume Issue Pages 481–485  
  Keywords (up)  
  Abstract Document classification usually requires of structural features such as the physical layout to obtain good accuracy rates on complex documents. This paper introduces a descriptor of the layout and a distance measure based on the cyclic dynamic time warping which can be computed in O(n2). This descriptor is translation invariant and can be easily modified to be scale and rotation invariant. Experiments with this descriptor and its rotation invariant modification are performed on the Girona archives database and compared against another common layout distance, the minimum weight edge cover. The experiments show that these methods outperform the MWEC both in accuracy and speed, particularly on rotated documents.  
  Address Barcelona, Spain  
  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 1520-5363 ISBN 978-1-4244-4500-4 Medium  
  Area Expedition Conference ICDAR  
  Notes DAG Approved no  
  Call Number DAG @ dag @ GoV2009a Serial 1175  
Permanent link to this record
 

 
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 (up)  
  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 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 Marçal Rusiñol; Josep Llados edit  url
doi  isbn
openurl 
  Title Logo Spotting by a Bag-of-words Approach for Document Categorization Type Conference Article
  Year 2009 Publication 10th International Conference on Document Analysis and Recognition Abbreviated Journal  
  Volume Issue Pages 111–115  
  Keywords (up)  
  Abstract In this paper we present a method for document categorization which processes incoming document images such as invoices or receipts. The categorization of these document images is done in terms of the presence of a certain graphical logo detected without segmentation. The graphical logos are described by a set of local features and the categorization of the documents is performed by the use of a bag-of-words model. Spatial coherence rules are added to reinforce the correct category hypothesis, aiming also to spot the logo inside the document image. Experiments which demonstrate the effectiveness of this system on a large set of real data are presented.  
  Address Barcelona; Spain  
  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 1520-5363 ISBN 978-1-4244-4500-4 Medium  
  Area Expedition Conference ICDAR  
  Notes DAG Approved no  
  Call Number DAG @ dag @ RuL2009b Serial 1179  
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Author Sergio Escalera; Alicia Fornes; O. Pujol; Petia Radeva; Gemma Sanchez; Josep Llados edit  doi
openurl 
  Title Blurred Shape Model for Binary and Grey-level Symbol Recognition Type Journal Article
  Year 2009 Publication Pattern Recognition Letters Abbreviated Journal PRL  
  Volume 30 Issue 15 Pages 1424–1433  
  Keywords (up)  
  Abstract Many symbol recognition problems require the use of robust descriptors in order to obtain rich information of the data. However, the research of a good descriptor is still an open issue due to the high variability of symbols appearance. Rotation, partial occlusions, elastic deformations, intra-class and inter-class variations, or high variability among symbols due to different writing styles, are just a few problems. In this paper, we introduce a symbol shape description to deal with the changes in appearance that these types of symbols suffer. The shape of the symbol is aligned based on principal components to make the recognition invariant to rotation and reflection. Then, we present the Blurred Shape Model descriptor (BSM), where new features encode the probability of appearance of each pixel that outlines the symbols shape. Moreover, we include the new descriptor in a system to deal with multi-class symbol categorization problems. Adaboost is used to train the binary classifiers, learning the BSM features that better split symbol classes. Then, the binary problems are embedded in an Error-Correcting Output Codes framework (ECOC) to deal with the multi-class case. The methodology is evaluated on different synthetic and real data sets. State-of-the-art descriptors and classifiers are compared, showing the robustness and better performance of the present scheme to classify symbols with high variability of appearance.  
  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 HuPBA; DAG; MILAB Approved no  
  Call Number BCNPCL @ bcnpcl @ EFP2009a Serial 1180  
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Author Sergio Escalera; Alicia Fornes; Oriol Pujol; Alberto Escudero; Petia Radeva edit  url
isbn  openurl
  Title Circular Blurred Shape Model for Symbol Spotting in Documents Type Conference Article
  Year 2009 Publication 16th IEEE International Conference on Image Processing Abbreviated Journal  
  Volume Issue Pages 1985-1988  
  Keywords (up)  
  Abstract Symbol spotting problem requires feature extraction strategies able to generalize from training samples and to localize the target object while discarding most part of the image. In the case of document analysis, symbol spotting techniques have to deal with a high variability of symbols' appearance. In this paper, we propose the Circular Blurred Shape Model descriptor. Feature extraction is performed capturing the spatial arrangement of significant object characteristics in a correlogram structure. Shape information from objects is shared among correlogram regions, being tolerant to the irregular deformations. Descriptors are learnt using a cascade of classifiers and Abadoost as the base classifier. Finally, symbol spotting is performed by means of a windowing strategy using the learnt cascade over plan and old musical score documents. Spotting and multi-class categorization results show better performance comparing with the state-of-the-art descriptors.  
  Address Cairo, Egypt  
  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 978-1-4244-5653-6 Medium  
  Area Expedition Conference ICIP  
  Notes MILAB;HuPBA;DAG Approved no  
  Call Number BCNPCL @ bcnpcl @ EFP2009b Serial 1184  
Permanent link to this record
 

 
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 (up)  
  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 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 (up)  
  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 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  
Permanent link to this record
 

 
Author Oriol Ramos Terrades; Ernest Valveny; Salvatore Tabbone edit  doi
openurl 
  Title Optimal Classifier Fusion in a Non-Bayesian Probabilistic Framework Type Journal Article
  Year 2009 Publication IEEE Transactions on Pattern Analysis and Machine Intelligence Abbreviated Journal TPAMI  
  Volume 31 Issue 9 Pages 1630–1644  
  Keywords (up)  
  Abstract The combination of the output of classifiers has been one of the strategies used to improve classification rates in general purpose classification systems. Some of the most common approaches can be explained using the Bayes' formula. In this paper, we tackle the problem of the combination of classifiers using a non-Bayesian probabilistic framework. This approach permits us to derive two linear combination rules that minimize misclassification rates under some constraints on the distribution of classifiers. In order to show the validity of this approach we have compared it with other popular combination rules from a theoretical viewpoint using a synthetic data set, and experimentally using two standard databases: the MNIST handwritten digit database and the GREC symbol database. Results on the synthetic data set show the validity of the theoretical approach. Indeed, results on real data show that the proposed methods outperform other common combination schemes.  
  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 0162-8828 ISBN Medium  
  Area Expedition Conference  
  Notes DAG Approved no  
  Call Number DAG @ dag @ RVT2009 Serial 1220  
Permanent link to this record
 

 
Author Ricard Coll; Alicia Fornes; Josep Llados edit  doi
isbn  openurl
  Title Graphological Analysis of Handwritten Text Documents for Human Resources Recruitment Type Conference Article
  Year 2009 Publication 10th International Conference on Document Analysis and Recognition Abbreviated Journal  
  Volume Issue Pages 1081–1085  
  Keywords (up)  
  Abstract The use of graphology in recruitment processes has become a popular tool in many human resources companies. This paper presents a model that links features from handwritten images to a number of personality characteristics used to measure applicant aptitudes for the job in a particular hiring scenario. In particular we propose a model of measuring active personality and leadership of the writer. Graphological features that define such a profile are measured in terms of document and script attributes like layout configuration, letter size, shape, slant and skew angle of lines, etc. After the extraction, data is classified using a neural network. An experimental framework with real samples has been constructed to illustrate the performance of the approach.  
  Address Barcelona, Spain  
  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 1520-5363 ISBN 978-1-4244-4500-4 Medium  
  Area Expedition Conference ICDAR  
  Notes DAG Approved no  
  Call Number DAG @ dag @ CFL2009 Serial 1221  
Permanent link to this record
 

 
Author Alicia Fornes; Josep Llados; Gemma Sanchez; Horst Bunke edit  isbn
openurl 
  Title Symbol-independent writer identification in old handwritten music scores Type Conference Article
  Year 2009 Publication In proceedings of 8th IAPR International Workshop on Graphics Recognition Abbreviated Journal  
  Volume Issue Pages 186–197  
  Keywords (up)  
  Abstract  
  Address La Rochelle, France  
  Corporate Author Thesis  
  Publisher Springer Berlin Heidelberg Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0302-9743 ISBN 978-3-642-13727-3 Medium  
  Area Expedition Conference GREC  
  Notes DAG Approved no  
  Call Number DAG @ dag @ FLS2009a Serial 1222  
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