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Frontiers of Information Technology & Electronic Engineering

ISSN 2095-9184 (print), ISSN 2095-9230 (online)

Visual knowledge guided intelligent generation of Chinese seal carving

Abstract: We digitally reproduce the process of resource collaboration, design creation, and visual presentation of Chinese seal-carving art. We develop an intelligent seal-carving art-generation system (Zhejiang University Intelligent Seal-Carving System, http://www.next.zju.edu.cn/seal/; the website of the seal-carving search and layout system is http://www.next.zju.edu.cn/seal/search_app/) to deal with the difficulty in using a visual knowledge guided computational art approach. The knowledge base in this study is the Qiushi Seal-Carving Database, which consists of open datasets of images of seal characters and seal stamps. We propose a seal character generation method based on visual knowledge, guided by the database and expertise. Furthermore, to create the layout of the seal, we propose a deformation algorithm to adjust the seal characters and calculate layout parameters from the database and knowledge to achieve an intelligent structure. Experimental results show that this method and system can effectively deal with the difficulties in the generation of seal carving. Our work provides theoretical and applied references for the rebirth and innovation of seal-carving art.

Key words: Seal-carving; Intelligent generation; Deep learning; Parametric modeling; Computational art

Chinese Summary  <18> 视觉知识引导的中国篆刻智能化生成

张克俊1,2,张瑞1,殷叶航1,李一非3,伍文棋1,孙凌云1,2,吴飞1,邓晃煌1,潘云鹤1
1浙江大学计算机科学与技术学院,中国杭州市,310027
2浙江大学―阿里巴巴前沿技术联合研究中心,中国杭州市,310027
3浙江大学软件学院,中国杭州市,310027
摘要:本文将传统篆刻艺术中的资源协同、设计创作、视觉呈现等过程以数字化方式再现,研制了篆刻艺术智能化创作的系统和平台(浙江大学智能篆刻系统:http://www.next.zju.edu.cn/seal/;篆刻搜索排版系统:http://www.next.zju.edu.cn/seal/search_app/),以视觉知识为引导突破计算机艺术学面临的难点问题。本文构建了包含字和印的求是篆刻数据库,并以此为视觉知识库,构建了篆字智能生成算法。此外,为创建印章布局,提出一种篆字变形算法调整印章字符,并结合视觉知识实现智能篆字布局,以实现智能结构。实验结果表明本文所提方法和系统可有效解决篆刻艺术生成中的难点问题,为篆刻艺术的守正与创新提供理论与应用借鉴。

关键词组:篆刻;智能生成;深度学习;参数化模型;计算机艺术


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DOI:

10.1631/FITEE.2100094

CLC number:

TP301.6

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On-line Access:

2022-10-24

Received:

2021-02-22

Revision Accepted:

2022-10-24

Crosschecked:

2021-06-20

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