基于分形维数和SVM的新疆民间艺术图案分类

J4 ›› 2011, Vol. 49 ›› Issue (02): 299-303.

基于分形维数和SVM的新疆民间艺术图案分类

赵海英^1,2, 冯月萍³, 彭宏¹

1. 新疆师范大学数理学院, 乌鲁木齐 830054|2. 北京科技大学信息工程学院, 北京 100083；3. 吉林大学计算机科学与技术学院, 长春 130012

收稿日期:2010-03-26 出版日期:2011-03-26 发布日期:2011-06-14
通讯作者: 冯月萍 E-mail:fengyp@jlu.edu.cn

ContentBased Xinjiang Folk Art Patterns ClassificationUsing Fractal Dimension and SVM

ZHAO Haiying^1,2, FENG Yueping³, PENG Hong¹

1. College of Computer Science and Technology, Xinjiang Normal University, Urumqi 830054, China;2. School of Information Engineering, University
of Science and Technology Beijing, Beijing 100083, China;3. College of Computer Science and Technology, Jilin University, Changchun 130012, China

Received:2010-03-26 Online:2011-03-26 Published:2011-06-14
Contact: FENG Yueping E-mail:fengyp@jlu.edu.cn

摘要/Abstract

摘要：

针对已有分类器存在的缺陷, 提出一种以分类错误率为标准选择组合特征的分类方法, 提高分类器的分类精度. 先提取图像的4种分形维数作为纹理特征, 再通过组合不同分形维数特征应用于支持向量机(SVM)进入样本训练阶段. 将分类错误率最低的特征组合作为分类器的特征向量, 应用于测试阶段的分类, 提高分类器的分类精度. 实验结果表明, 该方法具有较好的推广性, 为图像特征组合提取提供了新途径.

关键词: 分形维数；新疆民间艺术图案；支持向量机(SVM)；图案分类

Abstract:

To elucidate how to optimize combination features and to design a classifier with high classification accuracy, a challenging problem, a method based on error rate of classification as standard to select combined feature was presented so as to raise the classification accuracy. First, four kinds of f
ractal dimensions are extracted as texture features. Then, various combination features are training samples of SVM. With combination feature with the lowest classification error rate as a vector to be applied to the classification, the classification accuracy of the classifier can be improved. A variety of patterns are generated by primitive gene and regenerative gene. The proposed method is simple and easy in operation that can be widely popularized. So it can lay the foundation for the combination of image features.

Key words: fractal dimension, Xinjiang folk art patterns, support vector machine(SVM), image classification

中图分类号:

TP394.1

赵海英, 冯月萍, 彭宏. 基于分形维数和SVM的新疆民间艺术图案分类[J]. J4, 2011, 49(02): 299-303.

DIAO Hai-Yang, FENG Ru-Ping, BANG Hong. ContentBased Xinjiang Folk Art Patterns ClassificationUsing Fractal Dimension and SVM[J]. J4, 2011, 49(02): 299-303.