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A learning-based approach to cursive handwriting synthesis (2002).
| Content Provider | CiteSeerX |
|---|---|
| Author | Wang, Jue Wu, Chenyu Xu, Ying-Qing Shum, Heung-Yeung |
| Abstract | This paper proposes a learning-based approach to synthesize cursive handwriting of the user's personal handwriting style, by combining shape models and physical models together. In the training process, some sample paragraphs written by the user are collected and these cursive handwriting samples are segmented into individual characters by using a two-level writer-independent segmentation algorithm. Samples for each letter are then aligned and trained using Principal Component Analysis(PCA). In the synthesis process, a delta log-normal model based conditional sampling algorithm is proposed to produce smooth and natural cursive handwriting of the user's style from models. |
| File Format | |
| Publisher Date | 2002-01-01 |
| Access Restriction | Open |
| Subject Keyword | Cursive Handwriting Sample Synthesis Process Personal Handwriting Style Shape Model Conditional Sampling Algorithm Delta Log-normal Model Individual Character Cursive Handwriting Physical Model Sample Paragraph Training Process Learning-based Approach Natural Cursive Handwriting Two-level Writer-independent Segmentation Algorithm Principal Component Analysis Cursive Handwriting Synthesis |
| Content Type | Text |
| Resource Type | Article |
