Abstract
Handwriting-based writer identification is a hot research topic in the field of pattern recognition. Typically, there are four modes of writer identification: on-line text-dependent, on-line text-independent, off-line text-dependent, off-line text-independent; and off-line text-independent is the most challenging problem among them because many valuable writing features are not available in this case, such as shape features, dynastic writing information and etc. In this paper, we focus on the text-independent writer identification based on off-line Chinese handwriting and present a new contourlet-based GGD (Generalized Gaussian Density) method. This novel method achieves a good experiment result in our experiments.
| Original language | English |
|---|---|
| Pages (from-to) | 364-368 |
| Number of pages | 5 |
| Journal | Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics |
| Volume | 1 |
| State | Published - 2005 |
| Externally published | Yes |
| Event | IEEE Systems, Man and Cybernetics Society, Proceedings - 2005 International Conference on Systems, Man and Cybernetics - Waikoloa, HI, United States Duration: 10 Oct 2005 → 12 Oct 2005 |
Keywords
- Contourlet
- Gabor
- Generalized Gaussian Density
- Wavelet
- Writer identification
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