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An Image Retrieval Method Using DCT Features

机译:使用DCT特征的图像检索方法

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摘要

In this paper a new image representation for compressed domain image retrieval and an image retrieval system are presented. To represent images compactly arid hierarchically, multiple features such as color and texture features directly extracted from DCT coefficients are structurally organized using vector quantization. To train the codebook, a new Minimum Description Length vector quantization algorithm is used and it automatically decides the number of code words. To compare two images using the proposed representation, a new efficient similarity measure is designed. The new method is applied to an image database with 1,005 pictures. The results demonstrate that the method is better than two typical histogram methods and two DCT-based image retrieval methods.
机译:本文提出了一种用于压缩域图像检索的新图像表示和图像检索系统。为了紧凑,分层地表示图像,使用矢量量化在结构上组织了直接从DCT系数中提取的多个特征(例如颜色和纹理特征)。为了训练密码本,使用了新的最小描述长度矢量量化算法,该算法可以自动确定代码字的数量。为了使用建议的表示比较两个图像,设计了一种新的有效相似性度量。将该新方法应用于具有1,005张图片的图像数据库。结果表明,该方法优于两种典型的直方图方法和两种基于DCT的图像检索方法。

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