Title :
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
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;
Conference_Titel :
Document Analysis and Recognition, 2009. ICDAR '09. 10th International Conference on
Conference_Location :
Barcelona
Print_ISBN :
978-1-4244-4500-4
Electronic_ISBN :
1520-5363
DOI :
10.1109/ICDAR.2009.114
