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Author (up) 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  
  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.  
  Corporate Author Springer Verlag Thesis  
  Publisher Springer Verlag 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;IAM; Approved no  
  Call Number IAM @ iam @ MVA2000 Serial 1655  
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