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Author Josep Llados; Enric Marti edit  openurl
  Title A graph-edit algorithm for hand-drawn graphical document recognition and their automatic introduction into CAD systems Type Journal Article
  Year 1999 Publication Machine Graphics & Vision Abbreviated Journal  
  Volume 8 Issue Pages 195-211  
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  Notes DAG;IAM; Approved no  
  Call Number IAM @ iam @ LIM1999 Serial 1568  
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Author Josep Llados; Enric Marti edit  openurl
  Title Graph-edit algorithms for hand-drawn graphical document recognition and their automatic introduction Type Journal Article
  Year 1999 Publication Machine Graphics & Vision journal, special issue on Graph transformation Abbreviated Journal  
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  Notes DAG;IAM Approved no  
  Call Number IAM @ iam @ LIM1999c Serial 1569  
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Author Josep Llados; Enric Marti; Juan J.Villanueva edit  doi
openurl 
  Title Symbol recognition by error-tolerant subgraph matching between region adjacency graphs Type Journal Article
  Year 2001 Publication IEEE Transactions on Pattern Analysis and Machine Intelligence Abbreviated Journal  
  Volume 23 Issue 10 Pages 1137-1143  
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  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.  
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  Notes DAG;IAM;ISE; Approved no  
  Call Number IAM @ iam @ LMV2001 Serial 1581  
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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.  
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  Publisher Elsevier Science Inc. Place of Publication New York, NY, USA Editor  
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  Series Volume Series Issue Edition  
  ISSN 0167-8655 ISBN Medium  
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  Notes DAG; IAM Approved no  
  Call Number IAM @ iam @ VAM2003 Serial 1653  
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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  
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  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.  
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  Corporate Author Springer Verlag Thesis  
  Publisher Springer Verlag Place of Publication Editor  
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  Notes DAG;IAM; Approved no  
  Call Number IAM @ iam @ MVA2000 Serial 1655  
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