An effective method to detect and categorize digitized traditional Chinese paintings
An effective method to detect and categorize digitized traditional Chinese paintings
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DOI：
10.1016/j.patrec.2005.10.017
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发表时间：
2006-05-01
影响因子：
5.1
通讯作者：
Gao, W
中科院分区：
文献类型：
--
作者：
Jiang, SQ;Huang, QM;Gao, W
中国画是中国传统艺术的瑰宝。越来越多的TCP图像被数字化并在互联网上展示。有效地浏览和检索它们是一个需要解决的重要问题。工笔画和写意画是中国画的两种基本类型。本文提出了一种从普通图像中检测TCPs的方案，并将其分为工笔派和协益派。利用颜色直方图、颜色相关向量、自相关纹理特征和新提出的边缘大小直方图等低层特征实现高层分类。采用支持向量机作为主分类器，获得了令人满意的分类结果。实验结果表明了该方法的有效性。(C)2005 Elsevier B.V.保留所有权利。
Traditional Chinese painting (TCP) is the gem of Chinese traditional arts. More and more TCP images are digitized and exhibited on the Internet. Effectively browsing and retrieving them is an important problem that needs to be addressed. Gongbi (traditional Chinese realistic painting) and Xieyi (freehand style) are two basic types of traditional Chinese paintings. This paper proposes a scheme to detect TCPs from general images and categorize them into Gongbi and Xieyi schools. Low-level features such as color histogram, color coherence vectors, autocorrelation texture features and the newly proposed edge-size histogram are used to achieve the high-level classification. Support vector machine (SVM) is applied as the main classifier to obtain satisfactory classification results. Experimental results show the effectiveness of the method. (c) 2005 Elsevier B.V. All rights reserved.