| 基于小波提取特征的SVM目标识别 |
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| 引用本文： | 王明高,王琰.基于小波提取特征的SVM目标识别[J].沈阳理工大学学报,2006,25(5):35-38. |
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| 作者姓名： | 王明高 王琰 |
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| 作者单位： | 沈阳理工大学,信息科学与工程学院,辽宁,沈阳,110168 |
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| 摘 要： | 基于小波变换提出了一种特征提取及特征选择的方法.通过对小波系数绝对值化,减小了特征的分布范围;对小波进行自适应的过滤提取了目标的主要特征,增加了特征的聚类程度.本文通过SVM分类器对该方法进行验证并与其他方法比较.实验证明该方法有效的提高了目标的识别率,降低了误识别率.
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| 关 键 词： | 小波变换 SVM 特征提取 |
| 文章编号： | 1003-1251（2006）05-0035-04 |
| 收稿时间： | 2005-09-22 |
| 修稿时间： | 2005年9月22日 |
Object Recognition by SVM Based on Wavelet Feature Extraction |
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| WANG Ming-gao,WANG Yan.Object Recognition by SVM Based on Wavelet Feature Extraction[J].Transactions of Shenyang Ligong University,2006,25(5):35-38. |
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| Authors: | WANG Ming-gao WANG Yan |
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| Affiliation: | Shenyang Ligong University, Shenyang 110168, China |
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| Abstract: | In this paper,a method of feature selecting and feature extracting based on wavelet was proposed.Using this method the range of wavelet coefficients can be reduced by getting the absolute value of the coefficient;clustering the coefficient by filtering them with adaptive threshold.This method is tested by SVM classifier.Experimental results show that this method is effective for object recognition. |
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| Keywords: | wavelet transform SVM(support vector machine) feature extracting |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
