摘要
提出了一种基于小波变换和支持向量机的图像分类新方法,该方法利用小波变换进行图像特征提取,利用支持向量机进行图像分类,并与基于图像底层特征的分类方法进行了实验比较.实验结果表明该方法具有较好的分类性能.
A new method of image classification based on wavelet transformation and support vector machine is proposed, which employs wavelet transformation to extract features of the original images and then classifies them by support vector machine. A comparison between the proposed method and the one based on physical features of the image is presented. Experimental results show that the proposed method outperforms the others.
出处
《河北大学学报（自然科学版）》
CAS
北大核心
2007年第3期317-321,共5页
Journal of Hebei University(Natural Science Edition)
基金
国家自然科学基金资助项目(60573069)
河北省科技攻关资助项目(06213548)
关键词
图像
图像分类
特征提取
小波变换
支持向量机
image
image classification
feature extraction
wavelet transformation
support vector machine.
