• DocumentCode
    2149815
  • Title

    ICDAR 2011 Chinese Handwriting Recognition Competition

  • Author

    Liu, Cheng-Lin ; Yin, Fei ; Wang, Qiu-Feng ; Wang, Da-Han

  • Author_Institution
    Nat. Lab. of Pattern Recognition (NLPR), Beijing, China
  • fYear
    2011
  • fDate
    18-21 Sept. 2011
  • Firstpage
    1464
  • Lastpage
    1469
  • Abstract
    In the Chinese handwriting recognition competition organized with the ICDAR 2011, four tasks were evaluated: offline and online isolated character recognition, offline and online handwritten text recognition. To enable the training of recognition systems, we announced the large databases CASIA-HWDB/OLHWDB. The submitted systems were evaluated on un-open datasets to report character-level correct rates. In total, we received 25 systems submitted by eight groups. On the test datasets, the best results (correct rates) are 92.18% for offline character recognition, 95.77% for online character recognition, 77.26% for offline text recognition, and 94.33% for online text recognition, respectively. In addition to the evaluation results, we provide short descriptions of the recognition methods and have brief discussions.
  • Keywords
    handwriting recognition; handwritten character recognition; text analysis; CASIA-HWDB database; Chinese handwriting recognition competition; ICDAR 2011; OLHWDB database; character-level correct rate; offline handwritten text recognition; offline isolated character recognition; online handwritten text recognition; online isolated character recognition; Character recognition; Databases; Feature extraction; Handwriting recognition; Support vector machine classification; Text recognition; Training; Chinese handwriting recognition competition; handwritten text recognition; isolated character recongition; offline; online;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Document Analysis and Recognition (ICDAR), 2011 International Conference on
  • Conference_Location
    Beijing
  • ISSN
    1520-5363
  • Print_ISBN
    978-1-4577-1350-7
  • Electronic_ISBN
    1520-5363
  • Type

    conf

  • DOI
    10.1109/ICDAR.2011.291
  • Filename
    6065551