Chinese Handwriting Recognition Contest 2010

Abstract

Chinese handwriting recognition remains a challenge. Research works have reported very high accuracies on neatly handwritten characters yet the performance on unconstrained handwriting remains quite low. To promote the recognition technology, new databases of unconstrained handwriting have been constructed for academic research and benchmarking. This paper reports the contest results of online and offline handwritten Chinese character recognition using the new generation of databases, targeting 3,755 Chinese characters of the GB2312-80 first level set. Nine systems from four groups were submitted for evaluation. The best results are 92.39% accuracy for online character recognition and 89.99% accuracy for offline character recognition. Detailed analysis of results on data of different writers reveals the diversity of writing quality. The future contests will consider continuous script recognition as well as isolated character recognition.