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Author (up) Anders Hast; Alicia Fornes edit   pdf
doi  openurl
  Title A Segmentation-free Handwritten Word Spotting Approach by Relaxed Feature Matching Type Conference Article
  Year 2016 Publication 12th IAPR Workshop on Document Analysis Systems Abbreviated Journal  
  Volume Issue Pages 150-155  
  Abstract The automatic recognition of historical handwritten documents is still considered challenging task. For this reason, word spotting emerges as a good alternative for making the information contained in these documents available to the user. Word spotting is defined as the task of retrieving all instances of the query word in a document collection, becoming a useful tool for information retrieval. In this paper we propose a segmentation-free word spotting approach able to deal with large document collections. Our method is inspired on feature matching algorithms that have been applied to image matching and retrieval. Since handwritten words have different shape, there is no exact transformation to be obtained. However, the sufficient degree of relaxation is achieved by using a Fourier based descriptor and an alternative approach to RANSAC called PUMA. The proposed approach is evaluated on historical marriage records, achieving promising results.  
  Address Santorini; Greece; April 2016  
  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 DAS  
  Notes DAG; 602.006; 600.061; 600.077; 600.097 Approved no  
  Call Number HaF2016 Serial 2753  
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