Radical-based extract and recognition networks for Oracle character recognition
文献类型：期刊论文
| 作者 | Lin, Xiaoyu1; Chen, Shanxiong1,2; Zhao, Fujia1; Qiu, Xiaogang1 |
| 刊名 | INTERNATIONAL JOURNAL ON DOCUMENT ANALYSIS AND RECOGNITION
 |
| 出版日期 | 2022-04-13 |
| 页码 | 17 |
| 关键词 | Oracle radical MSER Attention mechanism Text detection and recognition |
| ISSN号 | 1433-2833 |
| DOI | 10.1007/s10032-021-00392-2 |
| 通讯作者 | Lin, Xiaoyu(linxiaoyu@email.swu.edu.cn) |
| 英文摘要 | The recognition of Oracle bone inscription (OBI) is one of the most fundamental aspect of OBI study. However, the complex glyph structure and many variants of OBI, which hinder the advancement of automatic recognition research. In order to solve these problems, this paper designs an Oracle radical extract and recognition framework(ORERF) based on deep learning. First, combining the maximally stable extremal regions(MSER) algorithm and self-defined post-processing algorithm to generate Oracle single radical data annotation; then, the generated Oracle radical-level annotation data set is input into the detection network, the detection network integrates multi-scale features, and uses the attention mechanism to implicitly extract Oracle single radical features, and then feeds the feature map to the detection module for radical detection; finally, we put the detected radicals to the auxiliary classifier network for recognition. The method of treating an OBI character as a composition of radicals rather than as a character category is a human-like method that can reduce the size of the vocabulary, ignore redundant information among similar characters. The experimental results are highlighted and compared to demonstrate the efficiency of the method. Furthermore, we also introduce two new datasets containing Oracle radical character dataset(ORCD) and Oracle combined-character dataset(OCCD). |
| 资助项目 | National Social Science Foundation[19BYY171] ; Key Laboratory of Oracle Information Processing of the Ministry of Education[OIP2019E009] |
| WOS研究方向 | Computer Science |
| 语种 | 英语 |
| WOS记录号 | WOS:000784010700001 |
| 出版者 | SPRINGER HEIDELBERG |
| 源URL | [http://119.78.100.138/handle/2HOD01W0/15542]  |
| 专题 | 中国科学院重庆绿色智能技术研究院 |
| 通讯作者 | Lin, Xiaoyu |
| 作者单位 | 1.Southwest Univ, Coll Comp & Informat Sci, Chongqing, Peoples R China 2.Chinese Acad Sci, Chongqing Inst Green & Intelligent Technol, Chongqing Key Lab Automated Reasoning & Cognit, Chongqing, Peoples R China |
| 推荐引用方式 GB/T 7714 | Lin, Xiaoyu,Chen, Shanxiong,Zhao, Fujia,et al. Radical-based extract and recognition networks for Oracle character recognition[J]. INTERNATIONAL JOURNAL ON DOCUMENT ANALYSIS AND RECOGNITION,2022:17. |
| APA | Lin, Xiaoyu,Chen, Shanxiong,Zhao, Fujia,&Qiu, Xiaogang.(2022).Radical-based extract and recognition networks for Oracle character recognition.INTERNATIONAL JOURNAL ON DOCUMENT ANALYSIS AND RECOGNITION,17. |
| MLA | Lin, Xiaoyu,et al."Radical-based extract and recognition networks for Oracle character recognition".INTERNATIONAL JOURNAL ON DOCUMENT ANALYSIS AND RECOGNITION (2022):17. |
入库方式： OAI收割
来源：重庆绿色智能技术研究院
浏览0
下载0
收藏0
其他版本
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。