CASIA Online and Offline Chinese Handwriting Databases

• Published in: 2011 International Conference on Document Analysis and Recognition pp. 37 - 41
• Main Authors: Cheng-Lin Liu, Fei Yin, Da-Han Wang, Qiu-Feng Wang
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.09.2011
• Subjects: Character recognition; Chinese handwriting databases; Handwriting recognition; handwritten texts; Image segmentation; isolated characters; offline; online; Text recognition; Training; Writing
• ISBN: 1457713500; 9781457713507
• ISSN: 1520-5363
• DOI: 10.1109/ICDAR.2011.17

This paper introduces a pair of online and offline Chinese handwriting databases, containing samples of isolated characters and handwritten texts. The samples were produced by 1,020 writers using Anoto pen on papers for obtaining both online trajectory data and offline images. Both the online samples and offline samples are divided into six datasets, three for isolated characters (DB1.0-C1.2) and three for handwritten texts (DB2.0-C2.2). The (either online or offline) datasets of isolated characters contain about 3.9 million samples of 7,356 classes (7,185 Chinese characters and 171 symbols), and the datasets of handwritten texts contain about 5,090 pages and 1.35 million character samples. Each dataset is segmented and annotated at character level, and is partitioned into standard training and test subsets. The online and offline databases can be used for the research of various handwritten document analysis tasks.