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基于颜色矩特征的图像检索：首先RGB颜色空间转换到HSV颜色空间；针对HSV三个分量计算颜色矩作为图像的内容特征；计算查询图像与图像库中每幅图像的相似距离，排序后给出检索结果。-Moment features based on color image retrieval : First RGB color space conversion to HSV color space; Three weight against HSV color calculated moments as images
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所谓基于内容图像的检索是指由图像分析软件对输入的图像先进行图像分析，根据图像中物体或区域的颜色(color)、形状(shape)或纹理(texture)等特征以及这些特征的组合，自动抽取特征，在将输入图像存入图像库的同时将其相应的特征向量也存入与图像库相连的特征库。-so-called content-based image retrieval is by image analysis software on the importation of the first images for ima
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matlab编程，基于颜色和纹理的图像检索算法的研究，思路清晰，方法有效。,matlab programming, based on the color and texture image retrieval algorithm is clearly thought effective.
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基于内容的图像检索技术，包含颜色特征及纹理特征matlab程序，实验结果-Content-based image retrieval, color features and texture features including matlab program, the experimental results
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基于颜色和纹理特征图像检索技术的研究，从CNKI上买来的，希望对大家有用！-Based on color and texture features of image retrieval research, from CNKI bought, and I hope useful for all of us!
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基于纹理特征和颜色直方图的内容图像检索源代码-Texture features based on color histogram and image retrieval of the contents of the source code
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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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近年来，随着互联网的高速发展，网上的多媒体信息也急剧增加，这些多媒体信息以图像为主。如何从浩瀚的图像数据库中快速、准确地找出所需要的图像，己成为一个备受关注的研究课题。有效地组织、管理和检索大规模的图像数据成为迫切需要解决的问题。于是基于内容的图像检索(Content-Based Image Retrieval: CBIR)作为一个崭新的研究领域出现了。
本课题拟研究、分析彩色图像红、绿、蓝三基色直方图的生成、特征提取和相似度等问题，应用图像的颜色信息—三基色直方图对图像进行检索。针对基于颜
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retrieval based on color feature has great practical value.
In this paper, the color distribution of endoscope image
in HSV color space is analyzed and a non-even color
quantification method is given, then all the endoscope
images’ color feat
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毕业设计，基于内容的图像检索，支持的检索特征包括 sift,颜色直方图，灰度矩阵，HU不变矩，边缘方向直方图，检索方法使用K-means和K-D树两种，需要OPENCV支持，运行时请先选定一个文件夹来生成特征库，特征库用access数据库保存，只支持JPG文件-Graduate design, content-based image retrieval, search features, including support sift, color histogram, gray matrix,
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介绍了一个基于特征的图象查询和检索系统.该系统由查询模块、特征提取和描述模块、匹配模块、图象显示模块和图象库管理模块组成.系统既支持基于颜色、纹理、形状的单一特征查询,也支持结合不同特征的更符合视觉要求的综合特征查询.该系统已结合实际图象库进行了查询和检索实验,文中给出一些实际检索结果.
-Describes a feature-based image query and retrieval system. The system consists of query module, featu
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Content-based medical image retrieval is now getting more and more attention in the
world, a feasible and efficient retrieving algorithm for clinical endoscopic images is urgently
required. Methods: Based on the study of single feature image retr
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一个Java实现的基于内容的图像检索工具包，可用来提取图像的颜色特征、纹理特征（Gabor Filter）以及形状特征，并在此基础上判断图像相关性。-Java implementation of a content-based image retrieval toolkit, which can be used to extract the image' s color features, texture features (Gabor Filter), and shape feature
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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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提出了一种新的基于区域的图像检索方法。与传统的基于区域的检索方法相比，论文从组成目标对象的基本结构角度出发分割图像，利用少量色彩等级更易描述对象主要构成的特性提取一组能够描述对象基本组成的区域序列。采用这些区域列的面积作为图像特征，用于图像检索。-A new region-based image retrieval. Traditional region-based retrieval methods, papers from the composition of the basic struc
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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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图像检索系统源码,仅用于商业学习!具体操作步骤如下：
1.输入带检索图像。
2.选择检索库路径。
3.选择检索方式：基于颜色特征、基于形状特征或者基于颜色和形状综合特征。
4.点击【开始检索】按钮即可得到检索结果。-The source of the image retrieval system, used only for commercial learning! Specific steps are as follows: 1. Input with retrieval of
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Color image retrieval technique based on color features and image bitmap,国外一片基于位图颜色空间实现检索的文章，相当不错。-Color image retrieval technique based on color features and image bitmap, bitmap-based foreign one color space to achieve retrieval of the article, is
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Image retri techniques are useful in many image-processing applications. Content-based image retri systems work with whole images and searching is based on comparison of the query. General techniques for image retri are color, texture and shape. Thes
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% 图像检索——纹理特征
%基于共生矩阵纹理特征提取，d=1,θ=0°,45°,90°,135°共四个矩阵
%所用图像灰度级均为256
%参考《基于颜色空间和纹理特征的图像检索》(% image retrieval - texture features
% based on co-occurrence matrix texture feature extraction, d=1, theta, =0 degrees, 45 degrees, 90 degrees, 135 degrees
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