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Author F. Javier Sanchez; Jordi Vitria; Enric Marti edit  openurl
  Title Transformaciones Morfológicas de Polígonos Isotéticos Type Conference Article
  Year 1991 Publication Primer Congreso Español de Informática Gráfica. Abbreviated Journal  
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  Area Expedition Conference  
  Notes OR;IAM;MV Approved (down) no  
  Call Number IAM @ iam @ SVM1991 Serial 1648  
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Author Gemma Sanchez; Josep Llados; Enric Marti edit  url
openurl 
  Title Segmentation and analysis of linial texture in plans Type Conference Article
  Year 1997 Publication Intelligence Artificielle et Complexité. Abbreviated Journal  
  Volume Issue Pages  
  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  
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  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference AERFAI  
  Notes DAG;IAM; Approved (down) no  
  Call Number IAM @ iam @ SLM1997 Serial 1649  
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Author Gemma Sanchez; Ernest Valveny; Josep Llados; Enric Marti; Oriol Ramos Terrades; N.Lozano; Joan Mas edit  openurl
  Title A system for virtual prototyping of architectural projects Type Conference Article
  Year 2003 Publication Proceedings of Fifth IAPR International Workshop on Pattern Recognition Abbreviated Journal  
  Volume Issue Pages 65-74  
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  Area Expedition Conference  
  Notes DAG;IAM Approved (down) no  
  Call Number IAM @ iam @ SVL2003 Serial 1650  
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Author Joan Serrat; Enric Marti edit  openurl
  Title Elastic matching using interpolation splines Type Conference Article
  Year 1991 Publication IV Spanish Symposium of Pattern Recognition and image Analysis Abbreviated Journal  
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  Notes ADAS;IAM; Approved (down) no  
  Call Number IAM @ iam @ SMV1991 Serial 1651  
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Author Elena Valderrama; Joan Oliver; Josep Maria-Basart; Enric Marti; Petia Radeva; Ricardo Toledo; R.Vilanova;F.Ced; J.Muñoz; S.Vacchina edit  openurl
  Title Convergencia al EEES de la ingeniería informática. Título de Grado en tecnología (Informática) Type Miscellaneous
  Year 2005 Publication I Jornades de Innovació Docent Abbreviated Journal  
  Volume Issue Pages  
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  Abstract Elena Valderrama  
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  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes IAM;RV;MILAB;ADAS Approved (down) no  
  Call Number IAM @ iam @ VOB2005 Serial 1652  
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Author Ernest Valveny; Enric Marti edit   pdf
doi  openurl
  Title A model for image generation and symbol recognition through the deformation of lineal shapes Type Journal Article
  Year 2003 Publication Pattern Recognition Letters Abbreviated Journal PRL  
  Volume 24 Issue 15 Pages 2857-2867  
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  Abstract We describe a general framework for the recognition of distorted images of lineal shapes, which relies on three items: a model to represent lineal shapes and their deformations, a model for the generation of distorted binary images and the combination of both models in a common probabilistic framework, where the generation of deformations is related to an internal energy, and the generation of binary images to an external energy. Then, recognition consists in the minimization of a global energy function, performed by using the EM algorithm. This general framework has been applied to the recognition of hand-drawn lineal symbols in graphic documents.  
  Address  
  Corporate Author Thesis  
  Publisher Elsevier Science Inc. Place of Publication New York, NY, USA Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0167-8655 ISBN Medium  
  Area Expedition Conference  
  Notes DAG; IAM Approved (down) no  
  Call Number IAM @ iam @ VAM2003 Serial 1653  
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Author Ernest Valveny; Enric Marti edit   pdf
doi  openurl
  Title Learning of structural descriptions of graphic symbols using deformable template matching Type Conference Article
  Year 2001 Publication Proc. Sixth Int Document Analysis and Recognition Conf Abbreviated Journal  
  Volume Issue Pages 455-459  
  Keywords  
  Abstract Accurate symbol recognition in graphic documents needs an accurate representation of the symbols to be recognized. If structural approaches are used for recognition, symbols have to be described in terms of their shape, using structural relationships among extracted features. Unlike statistical pattern recognition, in structural methods, symbols are usually manually defined from expertise knowledge, and not automatically infered from sample images. In this work we explain one approach to learn from examples a representative structural description of a symbol, thus providing better information about shape variability. The description of a symbol is based on a probabilistic model. It consists of a set of lines described by the mean and the variance of line parameters, respectively providing information about the model of the symbol, and its shape variability. The representation of each image in the sample set as a set of lines is achieved using deformable template matching.  
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  Area Expedition Conference  
  Notes DAG;IAM; Approved (down) no  
  Call Number IAM @ iam @ VMA2001 Serial 1654  
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Author Ernest Valveny; Enric Marti edit   pdf
doi  openurl
  Title Deformable Template Matching within a Bayesian Framework for Hand-Written Graphic Symbol Recognition Type Journal Article
  Year 2000 Publication Graphics Recognition Recent Advances Abbreviated Journal  
  Volume 1941 Issue Pages 193-208  
  Keywords  
  Abstract We describe a method for hand-drawn symbol recognition based on deformable template matching able to handle uncertainty and imprecision inherent to hand-drawing. Symbols are represented as a set of straight lines and their deformations as geometric transformations of these lines. Matching, however, is done over the original binary image to avoid loss of information during line detection. It is defined as an energy minimization problem, using a Bayesian framework which allows to combine fidelity to ideal shape of the symbol and flexibility to modify the symbol in order to get the best fit to the binary input image. Prior to matching, we find the best global transformation of the symbol to start the recognition process, based on the distance between symbol lines and image lines. We have applied this method to the recognition of dimensions and symbols in architectural floor plans and we show its flexibility to recognize distorted symbols.  
  Address  
  Corporate Author Springer Verlag Thesis  
  Publisher Springer Verlag Place of Publication Editor  
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  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes DAG;IAM; Approved (down) no  
  Call Number IAM @ iam @ MVA2000 Serial 1655  
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Author Ernest Valveny; Enric Marti edit   pdf
doi  isbn
openurl 
  Title Hand-drawn symbol recognition in graphic documents using deformable template matching and a Bayesian framework Type Conference Article
  Year 2000 Publication Proc. 15th Int Pattern Recognition Conf Abbreviated Journal  
  Volume 2 Issue Pages 239-242  
  Keywords  
  Abstract Hand-drawn symbols can take many different and distorted shapes from their ideal representation. Then, very flexible methods are needed to be able to handle unconstrained drawings. We propose here to extend our previous work in hand-drawn symbol recognition based on a Bayesian framework and deformable template matching. This approach gets flexibility enough to fit distorted shapes in the drawing while keeping fidelity to the ideal shape of the symbol. In this work, we define the similarity measure between an image and a symbol based on the distance from every pixel in the image to the lines in the symbol. Matching is carried out using an implementation of the EM algorithm. Thus, we can improve recognition rates and computation time with respect to our previous formulation based on a simulated annealing algorithm.  
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  Series Volume Series Issue Edition  
  ISSN ISBN 0-7695-0750-6 Medium  
  Area Expedition Conference  
  Notes DAG;IAM; Approved (down) no  
  Call Number IAM @ iam @ VAM2000 Serial 1656  
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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  
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  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 (down) no  
  Call Number IAM @ iam @ VAM1999a Serial 1657  
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