Online and offline handwritten Chinese character recognition: Benchmarking on new databases

CORC > 自动化研究所 > 中国科学院自动化研究所 > 模式识别国家重点实验室 > 模式分析与学习团队

	Online and offline handwritten Chinese character recognition: Benchmarking on new databases
	Liu, Cheng-Lin; Yin, Fei; Wang, Da-Han; Wang, Qiu-Feng
刊名	PATTERN RECOGNITION
	2013
卷号	46 期号:1 页码:155-162
关键词	Handwritten Chinese character recognition Online Offline Databases Benchmarking
英文摘要	Recently, the Institute of Automation of Chinese Academy of Sciences (CASIA) released the unconstrained online and offline Chinese handwriting databases CASIA-OLHWDB and CASIA-HWDB, which contain isolated character samples and handwritten texts produced by 1020 writers. This paper presents our benchmarking results using state-of-the-art methods on the isolated character datasets OLHWDB1.0 and HWDB1.0 (called DB1.0 in general), OLHWDB1.1 and HWDB1.1 (called DB1.1 in general). The DB1.1 covers 3755 Chinese character classes as in the level-1 set of GB2312-80. The evaluated methods include 1D and pseudo 2D normalization methods, gradient direction feature extraction from binary images and from gray-scale images, online stroke direction feature extraction from pen-down trajectory and from pen lifts, classification using the modified quadratic discriminant function (MQDF), discriminative feature extraction (DFE), and discriminative learning quadratic discriminant function (DLQDF). Our experiments reported the highest test accuracies 89.55% and 93.22% on the HWDB1.1 (offline) and OLHWDB1.1 (online), respectively, when using the MQDF classifier trained with DB1.1. When training with both the DB1.0 and DB1.1, the test accuracies on HWDB1.1 and OLHWDB are improved to 90.71% and 93.95%, respectively. Using DFE and DLQDF, the best results on HWDB1.1 and OLHWDB1.1 are 92.08% and 94.85%, respectively. Our results are comparable to the best results of the ICDAR2011 Chinese Handwriting Recognition Competition though we used less training samples. (C) 2012 Elsevier Ltd. All rights reserved.
WOS标题词	Science & Technology ; Technology
类目[WOS]	Computer Science, Artificial Intelligence ; Engineering, Electrical & Electronic
研究领域[WOS]	Computer Science ; Engineering
关键词[WOS]	FEATURE-EXTRACTION ; SHAPE NORMALIZATION
收录类别	SCI
语种	英语
WOS记录号	WOS:000309785000014
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/3092]
专题	自动化研究所_模式识别国家重点实验室_模式分析与学习团队
作者单位	Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit NLPR, Beijing 100190, Peoples R China
推荐引用方式 GB/T 7714	Liu, Cheng-Lin,Yin, Fei,Wang, Da-Han,et al. Online and offline handwritten Chinese character recognition: Benchmarking on new databases[J]. PATTERN RECOGNITION,2013,46(1):155-162.
APA	Liu, Cheng-Lin,Yin, Fei,Wang, Da-Han,&Wang, Qiu-Feng.(2013).Online and offline handwritten Chinese character recognition: Benchmarking on new databases.PATTERN RECOGNITION,46(1),155-162.
MLA	Liu, Cheng-Lin,et al."Online and offline handwritten Chinese character recognition: Benchmarking on new databases".PATTERN RECOGNITION 46.1(2013):155-162.