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CBIR is retrieval of images based on some query or example images. It is also called Query based image retrieval. Firstly, this report outlines a descr iption of the primitive features of an image color and shape. These features are extracted and use
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自己做的一个基于颜色的图像检索程序，采用分块+累加的方法，希望对你有用-Own a color-based image retrieval procedure, the use of block+ cumulative, and I hope useful to you
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基于颜色特征的图像检索系统，，做 了GUI节目，直观-Color-based Image Retrieval System, made a GUI program, intuitive
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基于不同特征的图像检索技术，颜色、纹理、形状、空间关系等特征提取的基础上，基于语义的图像检索技术-Different characteristics based image retrieval, color, texture, shape, spatial relations, feature extraction based on semantic-based image retrieval. Rar
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图像检索——提取颜色特征：HSV空间颜色直方图(将RGB空间转化为HSV空间并进行非等间隔量化，将三个颜色分量表示成一维矢量，再计算其直方图作为颜色特征。-Image Retrieval- extract color features: HSV space color histogram (RGB space into the HSV space and the non-interval to quantify the three color components expressed as a
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一个图像检索程序，使用VC6.0编译，基于颜色的，做图像处理的可以参考一下，很有意义-An image retrieval process, using VC6.0 compiler, based on color, do image processing for reference, it makes sense
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基于HSV颜色直方图和共生矩阵的邮票图像检索-Based on HSV color histogram and the co-occurrence matrix of the stamp image retrieval
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于内容的图像识别技术中．颜色自相关图是一种常用的图像颜色特征提取法。文章在此基础上，考虑图像
结构特征，通过对图像进行水平和垂直两次扫描．分别建立图像相似区域的变化图。该算法和颜色自相关图一并应用到
SOM网络上。实现了一个基于颜色特征和结构特征的图像分类。-Abstract：Many approaches for extracting color feature are widely used for content-based image retrieval．Each of them
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实现了一个由颜色特征和纹理特征进行加权组合的图像检索系统-To achieve a color features and texture features from the weighted combination of image retrieval system
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功能：求两幅图像的相似度，进而用于图像检索
尽管一幅彩色图像包含成千上万种颜色,但在多数情况下,图像中少数几种颜色就涵盖了图像中的大多数的象素颜色。这些颜色被称为主色。一些研究表明:使用主色一般不会降低颜色匹配效果。因此考虑一种次优可行的基于聚类颜色特征的相似度计算方法。
-Function: Find the similarity of two images, and then used for image retrieval although a color image con
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基于颜色矩和纹理谱的图像检索系统，可是实现准确率高的检索-Spectrum based on color moments and texture image retrieval system, but to achieve high accuracy of the retrieval
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Image segmentation systems have the potential to dramatically improve the performance of Digital image processing. Segmentation procedures partition an image into its constituent parts or objects. In general, segmentation is one of the most difficult
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Image segmentation systems have the potential to dramatically improve the performance of Digital image processing. Segmentation procedures partition an image into its constituent parts or objects. In general, segmentation is one of the most difficult
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Image segmentation systems have the potential to dramatically improve the performance of Digital image processing. Segmentation procedures partition an image into its constituent parts or objects. In general, segmentation is one of the most difficult
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Image segmentation systems have the potential to dramatically improve the performance of Digital image processing. Segmentation procedures partition an image into its constituent parts or objects. In general, segmentation is one of the most difficult
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Image segmentation systems have the potential to dramatically improve the performance of Digital image processing. Segmentation procedures partition an image into its constituent parts or objects. In general, segmentation is one of the most difficult
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Image segmentation systems have the potential to dramatically improve the performance of Digital image processing. Segmentation procedures partition an image into its constituent parts or objects. In general, segmentation is one of the most difficult
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Image segmentation systems have the potential to dramatically improve the performance of Digital image processing. Segmentation procedures partition an image into its constituent parts or objects. In general, segmentation is one of the most difficult
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有关于bmp图像，基于HSV 颜色空间的图像检索方法-Image retrieval method based on HSV color space
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Signature Based Approach For Image Retrieval
Using Color Histogram And Wavelet Transform
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