计算机应用与软件Issue(10)：209-212,4.DOI:10.3969/j.issn.1000-386x.2014.10.050
特征融合和支持向量机反馈的图像检索算法
IMAGE RETRIEVAL ALGORITHM BY INTEGRATING FEATURES FUSION AND SUPPORT VECTOR MACHINE FEEDBACK
摘要
Abstract
Retrieval algorithm is the basis of the massive image automatic retrieval.Since the single feature cannot accurately describe the image content,we propose an image retrieval algorithm by integrating the feature fusion and support vector machine feedback which combines the time domain features with frequency domain features.Firstly,the LBP histogram of the image is taken as the spatial features while the Brushlet transform is employed to extract the sub-band energy features to be the frequency domain features,then the Mahalanobis distance similarity measurement is used to make initial detection on the images,and finally the support vector machine feedback is adopted to improve the accuracy rate of image retrieval.Simulation results show that relative to the single feature retrieval algorithms,the proposed algorithm improves the average accuracy rate of the image retrieval,and can find the user desired image more accurately.关键词
图像检索/纹理特征/局部二值模式/Brushlet变换/支持向量机反馈Key words
Image retrieval/Texture feature/Local binary pattern/Brushlet transform/Support vector machine feedback分类
信息技术与安全科学引用本文复制引用
罗益荣..特征融合和支持向量机反馈的图像检索算法[J].计算机应用与软件,2014,(10):209-212,4.基金项目
湖南省科技计划项目（2011FJ3055）。 （）
