TY - JOUR
T1 - Coarse classification of on-line Chinese characters via structure feature-based method
AU - Lin, Tsai Zong
AU - Fan, Kuo Chin
N1 - Funding Information:
Acknowledgement--This work was supported in part by National Science Council of R.O.C. under grant NSC 82-0408-E-008-058.
PY - 1994/10
Y1 - 1994/10
N2 - In this paper, we will propose a structure feature-based coarse classification mechanism to classify the on-line handwritten Chinese characters. The main purpose of coarse classification is to classify on-line Chinese characters into one of the six structure types and divide them into separated parts accordingly, if they can be divided. Our proposed coarse classification mechanism can be used to classify the following three writing style categories: square writing characters, partial connected characters, and script characters. Two structure classification methods for coarse classification are proposed in this paper. One is the line segment order method, and another is the projection method. Fourteen databases of 5400 frequently used Chinese characters are tested in our experiment. The average classification rates of square writing characters, partial connected characters, and full connected characters are 96.7%, 92.8%, and 91.7%, respectively. The experimental results reveal the feasibility and promise of our proposed approach.
AB - In this paper, we will propose a structure feature-based coarse classification mechanism to classify the on-line handwritten Chinese characters. The main purpose of coarse classification is to classify on-line Chinese characters into one of the six structure types and divide them into separated parts accordingly, if they can be divided. Our proposed coarse classification mechanism can be used to classify the following three writing style categories: square writing characters, partial connected characters, and script characters. Two structure classification methods for coarse classification are proposed in this paper. One is the line segment order method, and another is the projection method. Fourteen databases of 5400 frequently used Chinese characters are tested in our experiment. The average classification rates of square writing characters, partial connected characters, and full connected characters are 96.7%, 92.8%, and 91.7%, respectively. The experimental results reveal the feasibility and promise of our proposed approach.
KW - Coarse classification
KW - Line segment order method
KW - Optical character recognition
KW - Projection method
UR - http://www.scopus.com/inward/record.url?scp=0028515932&partnerID=8YFLogxK
U2 - 10.1016/0031-3203(94)90070-1
DO - 10.1016/0031-3203(94)90070-1
M3 - 期刊論文
AN - SCOPUS:0028515932
SN - 0031-3203
VL - 27
SP - 1365
EP - 1377
JO - Pattern Recognition
JF - Pattern Recognition
IS - 10
ER -