DocumentCode :
1635492
Title :
An Investigation of Imaginary Stroke Techinique for Cursive Online Handwriting Chinese Character Recognition
Author :
Ding, Kai ; Deng, Guoqiang ; Jin, Lianwen
Author_Institution :
Coll. of Electron. & Inf., South China Univ. of Technol., Guangzhou, China
fYear :
2009
Firstpage :
531
Lastpage :
535
Abstract :
Imaginary stroke technique has been proved to be an effective solution to the problem of the stroke connection in online handwritten character recognition. However, it may cause confusions among characters with similar but actually different trajectories after adding imaginary strokes. In this paper, we first investigate both the benefit and the defect of the imaginary stroke technique, and then two modified methods are proposed under the framework of feature fusion and local feature enhance respectively. With the proposed methods, the feature of imaginary strokes is employed to unify the writing styles and the feature of real strokes is enhanced to strengthen discriminability. Experimental results for handwritten Chinese character recognition indicate that comparing with feature without imaginary strokes and feature with imaginary strokes, our proposed methods provide about 3%~8% and 1%~4% recognition accuracy improvement respectively.
Keywords :
feature extraction; handwritten character recognition; image enhancement; natural languages; cursive online handwriting Chinese character recognition; feature enhance; feature fusion; imaginary stroke technique; recognition accuracy improvement; writing style; Character recognition; Educational institutions; Handwriting recognition; Humans; Image analysis; Image recognition; Information analysis; Shape; Text analysis; Writing; Imaginary stroke technique; feature extraction; feature fusion; local feature enhance; online handwritten character recognition;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Document Analysis and Recognition, 2009. ICDAR '09. 10th International Conference on
Conference_Location :
Barcelona
ISSN :
1520-5363
Print_ISBN :
978-1-4244-4500-4
Electronic_ISBN :
1520-5363
Type :
conf
DOI :
10.1109/ICDAR.2009.29
Filename :
5277599
Link To Document :
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