[1]CHEN Xiao-e,CHEN Zhao-jiong.An application of multiclass SVM in the classification of artistic attributes of images[J].CAAI Transactions on Intelligent Systems,2009,4(2):157-162.
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An application of multiclass SVM in the classification of artistic attributes of images

CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume: 4 Number of periods: 2009 2 Page number: 157-162 Column: 综述 Public date: 2009-04-25
Title:
An application of multiclass SVM in the classification of artistic attributes of images
Author(s):
CHEN Xiao-e;  CHEN Zhao-jiong
College of Mathematics and Computer Science, Fuzhou University, Fujian 350108,China
Keywords:
SVM;  multiclass classification algorithm based on binary tree;  image artistic attributes
CLC:
TP391
DOI:
-
Abstract:
In image classification, few current classification algorithms classify images by their artistic attributes. An automatic image classification system based on artistic attributes was developed for classifying images in typical artistic styles such as photographs, Chinese paintings, watercolors, sketches, oil paintings, and so on. The system employed a support vector machine (SVM) as a classifier. Using a classification method at various levels, an SVM binary tree multiclass classification algorithm for image classification with respect to different artistic attributes was proposed. By analyzing the images with respect to the different artistic styles, some easily computed representative characteristics with good discriminability were extracted at each classification level. Experiments on a variety of characteristics at various levels and the total characteristics of classifiers were designed to evaluate the proposed classifier. Experimental results showed that the system has good classification performance.
References:
［1］毛大伟,张? 宏,童勤业.利用不同尺度下复杂性的差异区分文字和照片［J］. 计算机辅助设计与图形学学报,2005,17(8):18341838.
?MAO Dawei, ZHANG Hong, TONG Qinye. Image classification using Lempelziv complexity difference at different scale［J］. Journal of Computeraided Design & Computer Graphics, 2005, 17(8):18341838.
［2］王上飞，王熙法.图像情感检索研究的进展与展望［J］. 电路与系统学报, 2005, 10(4):102110.
?WANG Shangfei, WANG Xufa.Development and prospect on emotion image retrieval［J］. Journal of Circuits and Systems, 2005, 10(4):102110.
［3］ATHITSOS V, SWAIN M J, FRANKEL C. Distinguishing photographs and graphics on the world wide web［C］//Proc IEEE Workshop on ContentBased Access of Image and Video Libraries. Puerto Rico, 1997：1017.
［4］SZUMMER M, PICARD R W. Indooroutdoor image classification［C］//IEEE International Workshop on Contentbased Access of Image and Video Databases. Bombay, India，1998:4251.
［5］VAILAYA A, JAIN A, ZHANG H. On image classification:city ,vs landscape［J］. Pattern Recognition,1998,31 (12) :19211935.
［6］孟祥增,钟义信.WWW中图像的主题分类研究［J］. 情报杂志,2004,23(10):4757.
MENG Xiangzeng, ZHONG Yixin. Themebased classification of images in WWW［J］. Journal of Information，2004 23(10):4757.
［7］付 岩,王耀威,王伟强,高 文. SVM用于基于内容的自然图像分类和检索［J］.计算机学报，2003，26(10)：12611265.
?FU Yan, WANG Yaowei, WANG Weiqiang, GAO Wen. Contentbased natural image classification and retrieval using SVM［J］. Chinese Journal of Computers, 2003，26(10)：12611265.
［8］CUTZU F, HAMMOUD R, LEYKIN A. Distinguishing paintings from photographs［J］. Computer Vision and Image Understanding, 2005(100):249273.
［9］边肇祺,张学工.模式识别［M］.2版.北京:清华大学出版社,2004:284303.
［10】SANG H O, SUNGMOON C, SOO Y L. Support vector machines with binary tree architecture for multiclass classification［J］. Neural Information Processing Letters and Reviews, 2004,2(3):4751. 
［11］WESTON J, WATKINS C. Multiclass support vector machines［R］ .Technical Report CSDTR9804, Royal Holloway, Department of Computer Science,University of London,1998.
［12］HSU C W, LIN C J . A comparison of methods for multiclass support vector machines［J］. IEEE Transactions on Neural Networks,2002(13):415425.
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