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Evolution of multiple states machines for recognition of online cursive handwriting

Halavati, R ; Sharif University of Technology | 2006

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  1. Type of Document: Article
  2. DOI: 10.1109/WAC.2006.375750
  3. Publisher: IEEE Computer Society , 2006
  4. Abstract:
  5. Recognition of cursive handwritings such as Persian script is a hard task as there is no fixed segmentation and simultaneous segmentation and recognition is required. This paper presents a novel comparison method for such tasks which is based on a Multiple States Machine to perform robust elastic comparison of small segments with high speed through generation and maintenance of a set of concurrent possible hypotheses, The approach is implemented on Persian (Farsi) language using a typical feature set and a specific tailored genetic algorithm and the recognition and computation time is compared with dynamic programming comparison approach. Copyright - World Automation Congress (WAC) 2006
  6. Keywords:
  7. Computation theory ; Genetic algorithms ; Image segmentation ; Robust control ; Elastic pattern matching ; Evolutionary training ; Online handwriting recognition ; Pattern recognition
  8. Source: 2006 World Automation Congress, WAC'06, Budapest, 24 June 2006 through 26 June 2006 ; 2006 ; 1889335339 (ISBN); 9781889335339 (ISBN)
  9. URL: https://ieeexplore.ieee.org/document/4259823