DocumentCode :
1635009
Title :
A New Method for Rotation Free Method for Online Unconstrained Handwritten Chinese Word Recognition: A Holistic Approach
Author :
Ding, Kai ; Jin, Lianwen ; Gao, Xue
Author_Institution :
Coll. of Electron. & Inf., South China Univ. of Technol., Guangzhou, China
fYear :
2009
Firstpage :
1131
Lastpage :
1135
Abstract :
Most online handwriting word recognition (HWR) approaches proceed by segmenting words into isolate characters which are recognized separately. Inspired by results in cognitive psychology, holistic word recognition approaches provides another effective way to deal the problem of HWR. In this paper, we propose a new method for rotation free online unconstrained Chinese word recognition through a holistic approach. By a gravity center balancing skew detection and correction method, the rotation ranging from 0deg to 360deg of a Chinese handwritten word can be detected. Through the process of preprocessing, feature extraction using elastic meshing technique and classification, the handwritten words with characters even connected or partially overlapped can be recognized through a holistic approach. Experiments were performed on 8888 categories of 1,137,664 unconstrained handwritten Chinese word samples. Experimental results for randomly rotated unconstrained cursive handwritten Chinese word data demonstrated that the proposed method can achieve about 96.58% recognition accuracy.
Keywords :
feature extraction; handwritten character recognition; image classification; image segmentation; natural languages; HWR; cognitive psychology; correction method; elastic meshing technique; feature extraction; gravity center balancing skew detection; isolated character; online unconstrained handwritten chinese word recognition; rotation free method; word classification; word segmentation; Character recognition; Feature extraction; Gravity; Handwriting recognition; Humans; Information analysis; Personal digital assistants; Psychology; Shape; Text analysis; gravity center balancing; holistic word recognition; online handwriting word recognition; rotation free;
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.2009.30
Filename :
5277577
Link To Document :
بازگشت