|
|||||
|
|
| 基于分形维数和SVM的新疆民间艺术图案分类 | |
| 引用本文： | 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].吉林大学学报(理学版),2011,49(2):299-303. |
| 作者姓名： | 赵海英 冯月萍 彭宏 |
| 作者单位： | 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 |
| 基金项目： | 国家自然科学基金，新疆维吾尔自治区自然科学基金 |
| 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 |
| 收稿时间： | 2010-03-26 |
Content-Based Xinjiang Folk Art Patterns Classification Using Fractal Dimension and SVM |
|
| ZHAO Hai-ying,FENG Yue-ping,PENG Hong.Content-Based Xinjiang Folk Art Patterns Classification Using Fractal Dimension and SVM[J].Journal of Jilin University: Sci Ed,2011,49(2):299-303. | |
| Authors: | ZHAO Hai-ying FENG Yue-ping PENG Hong |
| Institution: | 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 |
| 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 thefoundation for the combination of image features. |
| Keywords: | fractal dimension Xinjiang folk art patterns support vector machine(SVM) image classification |
| 本文献已被 CNKI 万方数据 等数据库收录！ | |
| 点击此处可从《吉林大学学报(理学版)》浏览原始摘要信息 | |
| 点击此处可从《吉林大学学报(理学版)》下载免费的PDF全文 | |