Abstract
In the human society, it is very important to find out the true writer of an unknown handwriting document. Therefore handwriting-based writer identification has been a hot research topic in pattern recognition field since several decades before. In our research, we find that the global styles of different people's handwritings are obviously distinctive and the histogram of the wavelet coefficients of preprocessed handwriting image can be well characterized by the generalized Gaussian model (GGD) in wavelet domain. As a consequence, in this paper, we propose a new method by combining wavelet transform and GGD model for writer identification of Chinese handwriting document. Tested by our experiment, this method achieves a satisfied identification result and computational efficiency as well.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
