ICDAR 2011 Chinese Handwriting Recognition Competition
Published 1 September 2011
Cheng‐Lin Liu, Fei Yin, Qiufeng Wang, Da-Han Wang
Citations83
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TL;DR
In the Chinese handwriting recognition competition organized with the ICDAR 2011, four tasks were evaluated: offline and online isolated character recognition, offline and offline handwritten text recognition, and to enable the training of recognition systems, the large databases CASIA-HWDB/OLHW DB were announced.
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
Computer Science
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