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一种图像检索中纹理特征提取的方法。本文介绍了基于Gabor 滤波器和Gabor 小波变换提取纹理特征的分析方法, 以及对Gabor 小波进行了高斯归一化以提高对图像检索的速度和准确度。-An image retrieval texture feature extraction methods. This article based on Gabor filters and Gabor wavelet transform to extract texture feature analysis me
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基于自组织特征映射神经网络的图像压缩算法，ＥＩ检索论文，绝对有参考价值．-Based on self-organizing feature map neural network image compression algorithm, EI retrieval papers, the absolute reference value.
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Feature extraction is a key issue in contentbased
image retrieval (CBIR). In the past, a number of
texture features have been proposed in literature,
including statistic methods and spectral methods.
However, most of them are not able to accu
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基于颜色特征的图像检索，将颜色空间进行量化-To quantify color space image retrieval based on color feature,
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CBIR-Two novel contributions to Content Based Image Retrieval are presented and
discussed. The fi rst is a search engine for font recognition. The intended usage
is the search in very large font databases. The input to the search engine is a
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Two novel contributions to Content Based Image Retrieval are presented and
discussed. The fi rst is a search engine for font recognition. The intended usage
is the search in very large font databases. The input to the search engine is an
i
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基于图像内容的多维特征检索技术，主要利用图像的形状特征提取-Retrieval technique based on multi-dimensional characteristics of the image content, the main use of the shape of the image feature extraction
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Background of Content Based Image Retrieval(CBIR)
Analysis of Previous Work
Results of Existing Methods
Scalable Image Indexing and Retrieval
Proposed Indexing System(overview)
wavelet transform and HSL color conversion
Feature Space(Ener
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survey on content based medical image retrieval system it contains pre processing feature extraction and selection methods
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We review recent advances in image retri . The two fundamental
components of a retri system, representation and learning,
are analyzed. Each component is decomposed into its constituent
building blocks: features, feature representation, and sim
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This paper provides a comprehensive survey of the technical achievements in the
research area of image retri , especially content-based image retri , an area that
has been so active and prosperous in the past few years. The survey includes 100+
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