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| Writer Identification of Offline Chinese Handwriting Documents Based on Feature Fusion |
| YAN Yu-Chen,CHEN Qing-Hu,YUAN Feng,DENG Wei |
| School of Electronic Information,Wuhan University,Wuhan 430079 |
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Abstract A text-independent method for writer identification is proposed based on the fusion of text-dependent features. A two-factor model is developed, and thus the feature of handwriting is decomposed into the character factor and the writing factor. According to the deviation analysis of the two factors and data mining, the writing factor is separated, the text-independent feature based on text-dependent method is extracted, and the classifier is developed. The proposed method is effective for the samples with few characters, especially for the samples without the same characters between the unknown script and the corresponding one in the database. The proposed method provides a new way for writer identification with few characters in the writing sample.
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Received: 04 January 2009
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2010, Vol. 23 
