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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Wei Li Zhen Peng Pang Fei Sui |
| Copyright Year | 2009 |
| Abstract | Handwriting identification is one of the most important branches of computer vision and pattern recognition, and an effective means of identification that is important for surveillance and security, telecommunications, digital libraries, video meeting, and human-computer intelligent interactions. A deep research on pre-processing of Chinese handwriting identification is conducted in this paper. Computer can automatically find the threshold by using a new iteration algorithm in binarization, as it can retain more texture features of image. In noise eliminating, we also use an improved median filter to automatically determine the noise threshold, which is effective to get rid of the scattered noise. After experimentally repeated for many times in Matlab7.0, it’s proved that this preprocess is vary fast and stable. |
| Starting Page | 198 |
| Ending Page | 201 |
| File Size | 315622 |
| Page Count | 4 |
| File Format | |
| ISBN | 9780769536453 |
| DOI | 10.1109/CINC.2009.67 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2009-06-06 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Computer vision Noise reduction Adaptive filters Scattering Gray-scale pre-processing Telecommunication computing handwriting identification adaptive median filter binarization Image segmentation Software libraries Wiener filter Surveillance |
| Content Type | Text |
| Resource Type | Article |
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