CSRS: A Chinese Seal Recognition System With Multi-Task Learning and Automatic Background Generation
文献类型：期刊论文
| 作者 | Wang, Zhenyu1; Lian, Jie1; Song, Chunfeng2 ; Zheng, Wei1; Yue, Shaolong1; Ji, Senrong1
|
| 刊名 | IEEE ACCESS
 |
| 出版日期 | 2019 |
| 卷号 | 7页码:96628-96638 |
| 关键词 | Multi-task learning Siamese network Chinese seal recognition |
| ISSN号 | 2169-3536 |
| DOI | 10.1109/ACCESS.2019.2927396 |
| 通讯作者 | Wang, Zhenyu(zywang@ncepu.edu.cn) |
| 英文摘要 | As an important part of the Chinese painting and calligraphy, the seals not only have a high value of art but also contain a lot of information about the artwork itself. At this digital age, we would like not only be able to represent the seals in the digital format, but also like to use image processing techniques to help us better understand them. With the development of deep learning, convolutional neural networks have been widely used in the fields of feature learning, object localization, and classification. Based on deep learning technology, this paper proposes a highly accurate Chinese seal recognition system (CSRS). With our CSRS, users could simply input a single seal image into the system, then CSRS would automatically recognize the seal and report the relevant information in real-time. The CSRS mainly contains three units. 1) A new Siamese network with multi-task learning (Siamese-MTL), which can effectively solve the similarity measurement problem and improve the generalization of the model. 2) A new online data generation algorithm called automatic background generation (ABG) which could generate numerous seal images with different backgrounds for effective training. 3) A new training method for Siamese network which based on a central constraint. In order to validate the effectiveness of the proposed method, we have established two large scale seals image databases, including 15,000 Chinese seal images and 1,700 background images, respectively. We evaluate our method and compare with the variant methods on these datasets, achieving the highest performance. The extensive experimental results indicate that our proposed method is effective and has a great potential for the practical application in Chinese seals recognition. |
| WOS关键词 | SIAMESE NETWORK ; EXTRACTION |
| 资助项目 | National Natural Science Foundation of China[61573139] ; Fundamental Research Funds for the Central Universities[2018ZD05] |
| WOS研究方向 | Computer Science ; Engineering ; Telecommunications |
| 语种 | 英语 |
| WOS记录号 | WOS:000478961900102 |
| 出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
| 资助机构 | National Natural Science Foundation of China ; Fundamental Research Funds for the Central Universities |
| 源URL | [http://ir.ia.ac.cn/handle/173211/27532]  |
| 专题 | 自动化研究所_智能感知与计算研究中心 |
| 通讯作者 | Wang, Zhenyu |
| 作者单位 | 1.North China Elect Power Univ, Sch Control & Comp Engn, Beijing 102206, Peoples R China 2.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100080, Peoples R China |
| 推荐引用方式 GB/T 7714 | Wang, Zhenyu,Lian, Jie,Song, Chunfeng,et al. CSRS: A Chinese Seal Recognition System With Multi-Task Learning and Automatic Background Generation[J]. IEEE ACCESS,2019,7:96628-96638. |
| APA | Wang, Zhenyu,Lian, Jie,Song, Chunfeng,Zheng, Wei,Yue, Shaolong,&Ji, Senrong.(2019).CSRS: A Chinese Seal Recognition System With Multi-Task Learning and Automatic Background Generation.IEEE ACCESS,7,96628-96638. |
| MLA | Wang, Zhenyu,et al."CSRS: A Chinese Seal Recognition System With Multi-Task Learning and Automatic Background Generation".IEEE ACCESS 7(2019):96628-96638. |
入库方式： OAI收割
来源：自动化研究所
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