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首页> 外文期刊>International journal of image mining >Content-based image retrieval using SVD-based Eigen images
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Content-based image retrieval using SVD-based Eigen images

机译:使用基于SVD的特征图像进行基于内容的图像检索

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摘要

In this paper, a content-based image retrieval scheme using the singular value decomposition (SVD) is proposed where the feature vector was estimated from the selected significant components of a singular value decomposed image. The Eigen values of the decomposed image are divided into several numbers of groups and from each group we have constructed several Eigen images and subsequently, statistical values like mean, standard deviation and entropy are computed from those Eigen images. The constructed Eigen images are suitable to analyse the original image data in various image planes. This approach is applied to each colour components for formation of colour-based final feature vector. This approach is appropriate to reduce the overall processing cost in image retrieving process due to the consideration of significant image feature in SVD domain. The scheme is tested on a standard Corel image database and satisfactoryresults are achieved.
机译:在本文中,提出了一种使用奇异值分解(SVD)的基于内容的图像检索方案,其中,特征向量是从奇异值分解图像的选定有效分量中估算出来的。分解后的图像的特征值分为几个组,从每组中我们构造了几个特征图像,随后,从这些特征图像中计算出诸如均值,标准差和熵之类的统计值。构造的本征图像适合于分析各种图像平面中的原始图像数据。该方法应用于每种颜色分量,以形成基于颜色的最终特征向量。由于考虑了SVD域中的重要图像特征,因此该方法适合于降低图像检索过程中的总体处理成本。该方案在标准的Corel图像数据库上进行了测试,并获得了令人满意的结果。

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