ICDAR
2011
IEEE
13 years 1 days ago
2011
IEEE
—LDA transformation is one of the popular feature dimension reduction techniques for the feature extraction in most handwritten Chinese characters recognition systems. The integr...
ICDAR
2011
IEEE
13 years 1 days ago
2011
IEEE
—Radial harmonic Fourier moments (RHFMs) are invariant to translation, rotation, scaling and intensity, which own excellent image description ability, noise-resistant power, and ...
ICDAR
2009
IEEE
13 years 10 months ago
2009
IEEE
This paper presents a method for rotation free online handwritten Chinese character recognition (RFOHCCR). Given a skew online handwritten character sample, two orientation correc...
ICMI
2000
Springer
14 years 4 months ago
2000
Springer
- In this paper, we describe a new Chinese character recognition system, in which neural networks are employed as a nonlinear pre-classifier to pre-classify similar Chinese charact...
ICMI
2000
Springer
14 years 4 months ago
2000
Springer
For offline handwritten Chinese character recognition, stroke variation is the most difficult problem to be solved. A new method of optimal sampling features is proposed to compens...
ICPR
2008
IEEE
14 years 6 months ago
2008
IEEE
This paper proposes a new radical-based approach for online handwritten Chinese character recognition. The approach is novel in three respects: statistical classification of radic...
ICPR
2008
IEEE
14 years 6 months ago
2008
IEEE
This paper presents a new approach to largevocabulary online handwritten Chinese character recognition based on semi-tied covariance (STC) modeling. Detailed procedures are descri...
ICDAR
2009
IEEE
14 years 7 months ago
2009
IEEE
SIFT descriptor has been widely applied in computer vision and object recognition, but has not been explored in the field of handwritten Chinese character recognition. In this pap...
ICDAR
2009
IEEE
14 years 7 months ago
2009
IEEE
In this paper, we present a new method for on-line Chinese character recognition that relies on an explicit description of characters structure. Contrary to most of known structur...
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Lianwen Jin received a BS degree from the University of Science and Technology of China and a Ph.D. degree from South China University of Technology in 1991 and 1996, respectively....