DocumentCode :
2199060
Title :
SCUT-COUCH Textline_NU: An Unconstrained Online Handwritten Chinese Text Lines Dataset
Author :
Yan, Hanyu ; Jin, Lianwen ; Viard-gaudin, Christian ; Mouchère, Harold
Author_Institution :
Sch. of Electron. & Inf. Eng., South China Univ. of Technol., Guangzhou, China
fYear :
2010
fDate :
16-18 Nov. 2010
Firstpage :
581
Lastpage :
586
Abstract :
An unconstrained online handwritten Chinese text lines dataset, SCUT-COUCH Textline_NU, a subset of SCUT-COUCH [1] [2], is built to facilitate the research of unconstrained online Chinese text recognition. Texts for hand copying are sampled from China Daily corpus with a stratified random manner. The current vision of SCUT-COUCH Textline_NU has 8,809 text lines (4,813 lines are collected by touch screen LCD and 3,996 by digital pen) and 159,866 characters in total that are written by more than 157 participants. To demonstrate that the dataset is practical, an over-segmentation, dynamic programming and semantic model based algorithm was presented for segmenting and recognizing the unconstrained online Chinese text lines. In preliminary experiments on the dataset, the proposed algorithm recognition achieves a baseline accuracy of 56.41%.
Keywords :
dynamic programming; handwritten character recognition; image segmentation; natural languages; set theory; text analysis; China daily corpus; SCUT-COUCH textline NU; dynamic programming; handcopying; over-segmentation; semantic model based algorithm; subset; unconstrained online Chinese text recognition; unconstrained online handwritten Chinese textline dataset; SCUT-COUCH Textline_NU; online Chinese handwritten dataset; online Chinese text line recognition;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Frontiers in Handwriting Recognition (ICFHR), 2010 International Conference on
Conference_Location :
Kolkata
Print_ISBN :
978-1-4244-8353-2
Type :
conf
DOI :
10.1109/ICFHR.2010.123
Filename :
5693626
Link To Document :
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