A Novel Approach for Rotation Free Online Handwritten Chinese Character Recognition

Author

Huang, Shengming ; Jin, Lianwen ; Lv, Jin

Author_Institution

Sch. of Electron. & Inf., South China Univ. of Technol., Guangzhou, China

fYear

2009

Firstpage

1136

Lastpage

1140

Abstract

This paper presents a method for rotation free online handwritten Chinese character recognition (RFOHCCR). Given a skew online handwritten character sample, two orientation correction steps, including angle rectification according to the starting point, angle readjustment based on principal direction axes, are first performed to rectify the skew angle of the sample. Then 8-directional feature is extracted and the character is classified using the classifier trained by artificially rotated samples. Experiments on 863 online Chinese character dataset and SCUT-COUCH dataset show the effectiveness of the proposed approach.

Keywords

feature extraction; handwritten character recognition; image classification; image sampling; natural languages; Chinese character recognition; SCUT-COUCH dataset; feature extraction; image classification; image sampling; orientation correction step; rotation free online handwritten recognition; skew angle; Character recognition; Feature extraction; Flowcharts; Handwriting recognition; Information analysis; Testing; Text analysis;

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.2009.114

Filename

5277580