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基于综合特征和SVM相关反馈的图像检索
引用本文:吴凯,GU Shiwen,刘应龙.基于综合特征和SVM相关反馈的图像检索[J].现代电子技术,2008,31(16).
作者姓名:吴凯  GU Shiwen  刘应龙
作者单位:中南大学计算机信息与工程学院,湖南,长沙,410075
基金项目:国家自然科学基金重点资助项目
摘    要:提出综合纹理、颜色和形状特征的图像检索方法。首先采用Gabor小波计算ROIs(Regions of Interest)的位置和数目;然后在ROIs中,使用Gabor小波提取纹理特征,采用YUV空间直方图和颜色矩表示颜色特征,使用Zernike矩提取形状特征。为了提高图像检索的准确度,最后采用基于支持向量机(SVM)的相关反馈算法。实验结果表明,提出的方法具有较好的检索性能。

关 键 词:图像检索  特征提取  Zernike矩  纹理分析  相关反馈  支持向量机

Image Retrieval Based on Integrative Features and SVM Relevance Feedback
WU Kai,GU Shiwen,LIU Yinglong.Image Retrieval Based on Integrative Features and SVM Relevance Feedback[J].Modern Electronic Technique,2008,31(16).
Authors:WU Kai  GU Shiwen  LIU Yinglong
Abstract:The main focus in this paper is on integrated color,texture and shape extraction methods for CBIR.Original CBIR methodology that uses Gabor filtration for determining the number of Regions of Interest(ROIs).In the ROIs extracted,texture features based on thresholded Gabor features,color features based on histograms,color moments in YUV space,and shape features based on Zernike moments are then calculated.At last,an algorithm of the support vector machine for improving veracity of image retrieval is applied.The result of experiment illustrate proposed method have a better retrieval performance.
Keywords:image retrieval  feature extraction  Zernike moments  texture analysis  relevance feedback  support vector machine
本文献已被 CNKI 维普 万方数据 等数据库收录!
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