项目名称: 基于视觉感知和迁移学习的书法鉴别技术研究
项目编号: No.61202198
项目类型: 青年科学基金项目
立项/批准年度: 2013
项目学科: 计算机科学学科
项目作者: 郑霞
作者单位: 浙江大学
项目金额: 23万元
中文摘要: 书法作品鉴别是书法传承和保护中的重要环节。 然而,传统鉴别只局限于有限专家的个人经验,缺乏客观量化的实证,难以应对时下大批量作品辨真识伪的迫切需求。本课题以数字图像形式的书法作品为对象,展开基于视觉感知和迁移学习的书法鉴别技术研究,具体内容包括:(1)研究书法风格知识和书家个性知识,建立领域知识库;(2)研究书法作品图像的预处理技术;(3)遵循人眼视觉感知机理,基于统计学方法,用隐马尔科夫模型建立可计算的书法风格模型,用稀疏编码算法建立可计算的书家个性模型;(4)阐明书法鉴别的内部机理,建立书法鉴别的阶段模型:书法风格鉴别和书家个性鉴别;(5)采用迁移学习方法,研究基于小样本或稀缺样本的名家书法鉴别问题。本课题以建立通用的书法鉴别模型入手,梳理书法鉴别的层次结构和关系,研究具体实现技术,旨在为大规模书法鉴别的发展提供新思路和技术实践支持。
中文关键词: 视觉感知;艺术信息;中国书法鉴别;稀疏编码;
英文摘要: The authentication of chinese calligraphy works is an important part in the inheritance and protection for chinese calligraphy. However, traditional authentication, mostly depending on limited personal experience, lacks quantitative and objective evidence, hence can't meet the pressing need of authentication for large quantities of works. This project focuses on the digital form of works and explores the authentication technologies based on visual perception and transfer learning. The main contributions of this project are as follows:(1)According to research and analysis of calligraphy style and personalized calligraphy characteristic, domain knowledge databases are constructed. (2) The digital image preprocessing methods of calligraphy works are studied. (3) In reference to human visual perception mechanisms and on the basis of statistical methods, hidden Markov models are used to build the computable calligraphy style models. Besides, sparse coding models are used to build the computable personalized characteristic models. (4) After discussing the mechanism of calligraphy authentication, the project proposes and builds a two-stage authentication model consisting of calligraphy style verification and personalized characteristic identification. (5) For the calligraphists with scarcity works left, authentication
英文关键词: visual perception;artistic information;Chinses calligraphy authentication; sparse coding;