Chinese Handwriting Generation by Neural Network Based Style Transformation
文献类型：会议论文
| 作者 | Bi-Ren Tan1 ; Fei Yin1; Yi-Chao Wu1; Cheng-Lin Liu2
|
| 出版日期 | 2017-12 |
| 会议日期 | 2017年9月 |
| 会议地点 | 中国上海 |
| 关键词 | Handwriting Generation Style Transformation Neural Network Learning |
| 英文摘要 | This paper proposes a novel learning-based approach to generate personal style handwritten characters. Given some training characters written by an individual, we first calculate the deformation of corresponding points between the handwritten characters and standard templates, and then learn the transformation of stroke trajectory using a neural network. The transformation can be used to generate handwritten characters of personal style from standard templates of all categories. In training, we use shape context features as predictors, and regularize the distortion of adjacent points for shape smoothness. Experimental results on online Chinese handwritten characters show that the proposed method can generate personal-style samples which appear to be naturally written. |
| 会议录 | Springer
 |
| 学科主题 | 模式识别 |
| 语种 | 英语 |
| 源URL | [http://ir.ia.ac.cn/handle/173211/15621]  |
| 专题 | 自动化研究所_模式识别国家重点实验室_模式分析与学习团队 |
| 通讯作者 | Cheng-Lin Liu |
| 作者单位 | 1.中国科学院自动化研究所 2.中国科学院大学 |
| 推荐引用方式 GB/T 7714 | Bi-Ren Tan,Fei Yin,Yi-Chao Wu,et al. Chinese Handwriting Generation by Neural Network Based Style Transformation[C]. 见:. 中国上海. 2017年9月. |
入库方式： OAI收割
来源：自动化研究所
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