A handwritten Chinese character recognition system based on neural-fuzzy theory

2002 ◽  
Author(s):  
Hsin-Tai Yang ◽  
Jue-Wen Lin ◽  
Shie-Jue Lee
Keyword(s):  
Character Recognition ◽  
Chinese Character ◽  
Fuzzy Theory ◽  
Recognition System ◽  
Chinese Character Recognition ◽  
Handwritten Chinese Character Recognition ◽  
Neural Fuzzy

Research of Off-Line Handwritten Chinese Character Recognition System Based on Feedback Structure

2012 ◽  
Vol 433-440 ◽  
pp. 7046-7053 ◽  
Author(s):  
Jian Ping Wang ◽  
Hui Ying Cao ◽  
Jin Ling Wang ◽  
Cheng Hui Zhu
Keyword(s):  
Character Recognition ◽  
Chinese Character ◽  
Recognition System ◽  
Regulation Mechanism ◽  
Operating Mechanism ◽  
Chinese Character Recognition ◽  
Handwritten Chinese Character Recognition ◽  
Feedback Structure ◽  
The Operating Mechanism ◽  
Evaluation Mechanism

An offline handwritten Chinese character recognition system based on feedback structure is constructed. By imitating the feedback behavior in the human brain, the operating mechanism is presented. By comparing the recognition result character with the input character, four kinds of general characters recognition errors are defined. According to the analysis of the general errors, the evaluation mechanism and regulation mechanism of closed-loop based on feedback is made. Based on the trend of errors, the recognition process is adjusted to make the whole operating mechanism more reasonable. The results of simulation show that this system is efficient.

scholarly journals Efficient online handwritten Chinese character recognition system using a two-dimensional functional relationship model

2010 ◽  
Vol 20 (4) ◽  
pp. 727-738 ◽  
Author(s):  
Yun Chang ◽  
Jia Lee ◽  
Omar Rijal ◽  
Syed Bakar
Keyword(s):  
Character Recognition ◽  
Functional Relationship ◽  
Chinese Character ◽  
Graph Transformation ◽  
Recognition Rate ◽  
Recognition System ◽  
Two Dimensional ◽  
Chinese Character Recognition ◽  
Handwritten Chinese Character Recognition ◽  
Relationship Model

Efficient online handwritten Chinese character recognition system using a two-dimensional functional relationship modelThis paper presents novel feature extraction and classification methods for online handwritten Chinese character recognition (HCCR). TheX-graph andY-graph transformation is proposed for deriving a feature, which shows useful properties such as invariance to different writing styles. Central to the proposed method is the idea of capturing the geometrical and topological information from the trajectory of the handwritten character using theX-graph and theY-graph. For feature size reduction, the Haar wavelet transformation was applied on the graphs. For classification, the coefficient of determination (R2p) from the two-dimensional unreplicated linear functional relationship model is proposed as a similarity measure. The proposed methods show strong discrimination power when handling problems related to size, position and slant variation, stroke shape deformation, close resemblance of characters, and non-normalization. The proposed recognition system is applied to a database with 3000 frequently used Chinese characters, yielding a high recognition rate of 97.4% with reduced processing time of 75.31%, 73.05%, 58.27% and 40.69% when compared with recognition systems using the city block distance with deviation (CBDD), the minimum distance (MD), the compound Mahalanobis function (CMF) and the modified quadratic discriminant function (MQDF), respectively. High precision rates were also achieved.

Sign in / Sign up

Export Citation Format

Share Document