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
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