| 基于支持向量机的纸张缺陷图像分类识别 |
| |
| 引用本文： | 袁浩,付忠良,程建,阮波.基于支持向量机的纸张缺陷图像分类识别[J].计算机应用,2008,28(2):330-332,. |
| |
| 作者姓名： | 袁浩 付忠良 程建 阮波 |
| |
| 作者单位： | 1. 中国科学院,成都计算机应用研究所,成都,610041
2. 电子科技大学,电子工程学院,成都,610054 |
| |
| 摘 要： | 根据支持向量机（SVM）在小样本、高维模式分类中具有的优良分类性能，提出将支持向量机应用于实际的纸张缺陷分类。针对三种现场易出现的缺陷，通过对缺陷图像进行预处理、特征选择，再利用SVM进行分类，利用交叉验证进行参数和模型选取，取得了较好的分类效果，为纸张缺陷的分类指出一种可行的方法。
|
| 关 键 词： | 支持向量机 纸张缺陷 分类识别 特征选择 |
| 文章编号： | 1001-9081（2008）02-0330-03 |
| 收稿时间： | 2007-08-10 |
| 修稿时间： | 2007-10-10 |
Paper sheet defects classification based on support vector machine method |
| |
| YUAN Hao,FU Zhong-liang,CHENG Jian,RUAN Bo.Paper sheet defects classification based on support vector machine method[J].journal of Computer Applications,2008,28(2):330-332,. |
| |
| Authors: | YUAN Hao FU Zhong-liang CHENG Jian RUAN Bo |
| |
| Affiliation: | YUAN Hao1,FU Zhong-liang1,CHENG Jian2,RUAN Bo1(1.Chengdu Institute of Computer Application,Chinese Academy of Sciences,Chengdu Sichuan 610041,China,2.School of Electronic Engineering,University of Electronic Science , Technology of China,Chengdu Sichuan 610054,China) |
| |
| Abstract: | We proposed a paper sheet defects classification method based on SVM according to its good performance in small data sets and high dimension feature spaces. To classify three common defects of the paper sheet, we firstly preprocessed the defect images, then carefully selected the input features for training the SVM-based classifiers, and optimized the parameters and the classifiers by the cross-validation method. The results prove that SVM is practical in paper sheet defects classification and identification. |
| |
| Keywords: | Support Vector Machine(SVM) paper sheet defect classification and recognition feature selection |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
| 点击此处可从《计算机应用》浏览原始摘要信息 |
|
点击此处可从《计算机应用》下载全文 |
|
