摘要
目前针对中国画的研究主要集中在基于内容的图像分析上,但是对于中国画的分类识别,更重要的是艺术风格而非内容.中国画的本质是笔墨运用,笔道的线条形状和墨色构成是鉴别艺术风格的重要因素.因此,文中提出基于笔墨特征的中国画画家识别算法.首先提取墨线的形状特征和墨色的布局特征,然后综合上述2种特征,作为支持向量机的输入训练得到画作分类器.实验表明,文中算法在平均查全率和查准率上较优,可以用于中国画的数字化分析、理解和识别,为中国画传承和鉴赏提供有效的数字工具.
Most of the existing Chinese paintings research focuses on the content rather than the artistic style. Since the essence of Chinese paintings is represented by brushwork and ink, different artists can be normally identified by the style of their brushwork. In this paper, an algorithm is proposed to classify Chinese paintings based on brushwork and ink. The line shape feature and the ink color distribution feature are described. Combining these two features, a complex character is established. And the complex character is used as the input of the support vector machines classifier. Extensive experiments show that the average recall and precision of the proposed algorithm are higher than those of the representative existing benchmarks, including MHMM, C4. 5 and Fusion. The proposed algorithm can be used for the digital analysis, management, understanding and identification of Chinese paintings. Moreover, it provides an effective digital tool for the inheritance and appreciation of Chinese painting.
出处
《模式识别与人工智能》
EI
CSCD
北大核心
2017年第10期917-927,共11页
Pattern Recognition and Artificial Intelligence
基金
国家自然科学基金项目(No.61502331)
天津市自然科学基金项目(No.15JCQNJC00800
16JCYBJC42000)
中国民航信息技术科研基地开放课题(No.CAAC-ITRB-201504)资助~~
关键词
中国画分类
方向梯度直方图
主方向墨色
线条形状
特征提取
Classification of Chinese Paintings, Histogram of Oriented Gradient, Ink Color of Principal Direction, Line Shape, Feature Extraction
