Modified Quadratic Discriminant Functions and the Application to Chinese Character Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Handbook of Computer Vision Algorithms in Image Algebra
Handbook of Computer Vision Algorithms in Image Algebra
Digital Image Processing
A Fast HMM Algorithm for On-line Handwritten Character Recognition
ICDAR '97 Proceedings of the 4th International Conference on Document Analysis and Recognition
Recognizing on-line handwritten Chinese character via FARG matching
ICDAR '97 Proceedings of the 4th International Conference on Document Analysis and Recognition
ICDAR '97 Proceedings of the 4th International Conference on Document Analysis and Recognition
ICPR '96 Proceedings of the International Conference on Pattern Recognition (ICPR '96) Volume III-Volume 7276 - Volume 7276
Recognition Algorithm Based on Wavelet Transform for Handprinted Chinese Characters
ICPR '98 Proceedings of the 14th International Conference on Pattern Recognition-Volume 1 - Volume 1
Multiresolution Recognition of Offline Handwritten Chinese Characters with Wavelet Transform
ICDAR '01 Proceedings of the Sixth International Conference on Document Analysis and Recognition
Handwritten Chinese Character Recognition: Alternatives to Nonlinear Normalization
ICDAR '03 Proceedings of the Seventh International Conference on Document Analysis and Recognition - Volume 1
On-line Overlaid-Handwriting Recognition Based on Substroke HMMs
ICDAR '03 Proceedings of the Seventh International Conference on Document Analysis and Recognition - Volume 2
Online Recognition of Chinese Characters: The State-of-the-Art
IEEE Transactions on Pattern Analysis and Machine Intelligence
Principal Component Analysis for Online Handwritten Character Recognition
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 2 - Volume 02
Global Shape Normalization for Handwritten Chinese Character Recognition: A New Method
IWFHR '04 Proceedings of the Ninth International Workshop on Frontiers in Handwriting Recognition
An improved handwritten Chinese character recognition system using support vector machine
Pattern Recognition Letters - Special issue: Artificial neural networks in pattern recognition
ICDAR '05 Proceedings of the Eighth International Conference on Document Analysis and Recognition
ICDAR '05 Proceedings of the Eighth International Conference on Document Analysis and Recognition
Moment normalization of handprinted characters
IBM Journal of Research and Development
WSEAS Transactions on Mathematics
Image quality assessment: from error visibility to structural similarity
IEEE Transactions on Image Processing
International Journal of Applied Mathematics and Computer Science
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This paper presents novel feature extraction and classification methods for online handwritten Chinese character recognition (HCCR). The X-graph and Y-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 the X-graph and the Y-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.