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Title:
an approach for real-time recognition of online chinese handwritten sentences
Author: Wang Da-Han ; Liu Cheng-Lin ; Zhou Xiang-Dong
Source: Pattern Recognition
Issued Date: 2012
Volume: 45, Issue:10, Pages:3661-3675
Indexed Type: ei
Department: (1) National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, 95 Zhongguan East Road, Beijing 100190, China; (2) Intelligence Engineering Lab, Institute of Software, Chinese Academy of Sciences, P.O. Box 8718, Beijing 100190, China
English Abstract: With the advances of handwriting capturing devices and computing power of mobile computers, pen-based Chinese text input is moving from character-based input to sentence-based input. This paper proposes a real-time recognition approach for sentence-based input of Chinese handwriting. The main feature of the approach is a dynamically maintained segmentation-recognition candidate lattice that integrates multiple contexts including character classification, linguistic context and geometric context. Whenever a new stroke is produced, dynamic text line segmentation and character over-segmentation are performed to locate the position of the stroke in text lines and update the primitive segment sequence of the page. Candidate characters are then generated and recognized to assign candidate classes, and linguistic context and geometric context involving the newly generated candidate characters are computed. The candidate lattice is updated while the writing process continues. When the pen lift time exceeds a threshold, the system searches the candidate lattice for the result of sentence recognition. Since the computation of multiple contexts consumes the majority of computing and is performed during writing process, the recognition result is obtained immediately after the writing of a sentence is finished. Experiments on a large database CASIA-OLHWDB of unconstrained online Chinese handwriting demonstrate the robustness and effectiveness of the proposed approach. © 2012 Elsevier Ltd.
Language: 英语
WOS ID: WOS:000305845300008
Citation statistics:
Content Type: 期刊论文
URI: http://ir.iscas.ac.cn/handle/311060/14739
Appears in Collections:软件所图书馆_期刊论文

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Recommended Citation:
Wang Da-Han,Liu Cheng-Lin,Zhou Xiang-Dong. an approach for real-time recognition of online chinese handwritten sentences[J]. Pattern Recognition,2012-01-01,45(10):3661-3675.
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