中国画的计算机分析与分类算法研究

项目名称： 中国画的计算机分析与分类算法研究

项目编号： No.61502331

项目类型： 青年科学基金项目

立项/批准年度： 2016

项目学科： 计算机科学学科

项目作者： 盛家川

作者单位： 天津财经大学

项目金额： 21万元

中文摘要： 中国画数字化正迅猛发展，近年来随着数字博物馆技术的发展，国画图像分析处理越来越重要。目前针对中国画的计算机数字分析还处于探索阶段，存在两点不足1）大多是基于内容的检索和分析，而中国画艺术元素有限，仅仅依据图像内容的比较不能达到很好的识别效果；2）水墨画渲染研究中大多是单独笔道的仿真研究。针对以上问题，本项目将1）对中国画中的主要艺术元素进行分割，进而对其艺术风格在像素域和变换域进行数字量化、分析和深度优化，提炼出最能体现画家个人风格的高级语义信息；2）将复合特征提取加入嵌入式学习的过程中，提出基于嵌入式学习的多核一类支持向量机对国画的艺术风格、作者进行自动分类；3）研究自适应的多源信息融合算法，将识别结果进行有机的融合，优化计算机对中国画的分析、理解的准确度。本项目将计算机与画家的创造性思维相结合，其研究将实现国画的数字化分析、识别和管理，为文化艺术的传承、鉴赏提供理论和技术支持。

中文关键词： 中国画分类；艺术画分析与识别；；嵌入式机器学习；一类支持向量机；特征提取

英文摘要： Digital arts are becoming increasingly important over the past few years along with the enormous advancement of digital technology application upon Chinese paintings. At present, computerized analysis on Chinese paintings is limited to two points of weakness: (i) directly applying image processing techniques to carry out content-based search or analysis, and such approach often fails due to the fact that the content of Chinese paintings is limited with significant level of similarities among those basic elements, such as mountains, trees, etc. (ii) current research on computerized Chinese paintings is mostly limited to simulation of individual strokes and feature extractions, which often fail to capture the creative nature of Chinese arts as well as the varying styles. This proposal will resolve the above problems according to the following approaches, which can be highlighted as: (i) description and representation of Chinese painting styles to capture their essential creative elements and hence provide high-level characterization of Chinese paintings and artistic style features; (ii) development of new approaches in extracting multiple and integrated digital features to drive a multi-kernel one class SVM and facilitate an embedded learning process to complete automated classification and recognition. Such approach will produce powerful digital tools and enable Chinese artists to increase their effectiveness of creative arts; (iii) extensive research is to be carried out on developing self-adaptive multi-source fusion algorithms to increase the level of precision in analysing and understanding Chinese paintings to exploit the embedded learning process out of multiple and integrated feature analysis. The proposed project will have a range of impacts and values, which include: (i) combination of computerized analysis and creative arts to explore a new field of research on digital arts; (ii) digitalization of Chinese arts towards computerized analysis, recognition and management of national heritages; and (iii) provision of computing support for cultural and artistic inheritance as well as theoretical developments.

英文关键词： Classification of Chinese paintings;Computerized analysis of Chinese arts;Embedded machine learning;One-class SVM;Feature extraction