Description: 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 of features; Inquiries calculated images and image repository, each image is similar distance, is sorting search results. Platform: |
Size: 2080768 |
Author:吴成玉 |
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Description: 一种基于HSV颜色空间的图像检索技术
随着大规模数字图像库的出现，基于内容的图像检索技术（CBIR）应运而生。而颜色特征是在图像检索中应用最为广泛的视觉特征，因此设计并实现一个基于颜色的图像检索系统具有一定的前沿性和实用性-an HSV color space-based image retrieval technology with the massive digital image library there. Content-Based Image Retrieval (CBIR) came into being. And color features in image retrieval application of the most extensive visual characteristics, Therefore the design and realization of a color-based image retrieval system with a front and practicality Platform: |
Size: 94208 |
Author:guoxiaoyong |
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Description: 针对目前的基于特征的图像检索中没有有效地结合图像中对象空间信息的问题，提
出了一种新的融合了颜色、空间和纹理特征的图像特征提取及匹配方法。为了减少时间
间复杂度，首先通过基于普通颜色直方图的检索得到初始图像集合，然后根据提出的结合空间、纹理特征加权度量对初始图像集合再进行检索，从而得到最后更符合要求的相似图象-View of the current feature-based image retrieval is not effective integration of image information of objects in space, we propose a new blend of colors, space and texture features of image feature extraction and matching method. Time interval in order to reduce complexity, first of all, the general color histogram-based retrieval has been the initial image set, and then on the basis of the combination of space, texture characteristics of the weighted measure of the initial image and then search the collection, thus more in line with the requirements of the final similarity Image Platform: |
Size: 9111552 |
Author:丁丁 |
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Description: 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! Platform: |
Size: 338944 |
Author:李自凯 |
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Description: 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 Platform: |
Size: 185344 |
Author:tianyun |
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Description: 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 accurately capture
the edge information which is the most important texture
feature in an image. Recent researches on multi-scale
analysis, especially the curvelet research, provide good
opportunity to extract more accurate texture feature for
image retrieval. Curvelet was originally proposed for
image denoising and has shown promising performance.
In this paper, a new image feature based on curvelet
transform has been proposed. We apply discrete curvelet
transform on texture images and compute the low order
statistics from the transformed images. Images are then
represented using the extracted texture features. Retrieval
results show, it significantly outperforms the widely used
Gabor texture feature. Platform: |
Size: 1426432 |
Author:Swati |
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Description: 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。针对基于颜色的图像检索，本文采用应用广泛的RGB颜色空间来表示图像的颜色特征，对颜色分量进行等间隔量化并形成特征矢量并对特征矢量进行归一化处理，采用图像均匀分块的方法引入图像中色彩所处的位置信息，用距离度量函数进行图像的相似性匹配。在此基础上实现了基于三基色直方图算法的检索系统。
本文的研究和实践对于促进基于内容的图像数据库检索技术的应用具有一定的参考价值和实践意义。-With the rapid development of Internet, the multimedia information is booming. All this information is mostly images. Effective recognizing, management and searching all these images have been an emergent problem. This has led the rise of a new research and development field: Content-Based Image Retrieval (CBIR).
The topics to research, analysis color images red, green and blue color histogram generation, feature extraction and the similarity of the issues, application of the color image- trichromatic histogram of the image retrieval. Based on the color against the static image retrieval, this paper application of a wide range of RGB color space to indicate the color image features, the color components, such as spacing and quantitative characteristics of a feature vector and a normalization of vector processing, using uniform image block the introduction of the method in which the color image Location information, and distance measuring function similar to the image of the match. On Platform: |
Size: 408576 |
Author:qichao |
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Description: 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 features are extracted. At last three
experiments are designed to prove the validity of these
methods in endoscope image retrieval. Platform: |
Size: 1024 |
Author:rach |
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Description: 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, HU moment invariants, edge direction histogram, retrieval method using the K-means and KD trees are two kinds of needs OPENCV support Please select a runtime folder to generate the feature library, feature library with access database save, only supports JPG files Platform: |
Size: 359424 |
Author:平天羽 |
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Description: 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, feature extraction and description of the module, matching module, image display module and image database management module. System not only supports color, texture, shape single feature queries, and also supports a combination of different features more in line with requirements of the integrated features of the visual query. The system has been carried out with the actual image database query and retrieval experiments, the paper gives some actual search results. Platform: |
Size: 100352 |
Author:陈怡 |
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Description: 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 retrieving techniques, including color
clustering, color texture and shape, a new retrieving method with multi-features fusion and relevance
feedback is proposed to retrieve the desired endoscopic images. Results: A prototype system is set
up to evaluate the proposed method’s performance and some evaluating parameters such as the
retrieval precision & recall, statistical average position of top 5 most similar image on various features, etc.
are therefore given. Conclusions: The algorithm with multi-features fusion and relevance feedback
gets more accurate and quicker retrieving capability than the one with single feature image retrieving
technique due to its flexible feature combination and interactive relevance feedback. Platform: |
Size: 359424 |
Author:gokul/goks |
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Description: 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 features, and on this basis to determine the image correlation. Platform: |
Size: 41984 |
Author:杜可 |
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Description: 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 description of the primitive features of an image color and shape. These features are extracted and used as the basis for a similarity check between images. The final result is a MatLab built software application, with an image database, that utilized color and shape features of the images in the database as the basis of comparison and retrieval. Platform: |
Size: 304128 |
Author:keerthi |
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Description: 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 structure of the target image segmentation perspective, using a small amount of color more likely to describe the object level of the main components of the feature extraction to describe a group of objects composed of basic region sequences. The use of these areas out of the area as image features for image retrieval. Platform: |
Size: 343040 |
Author:lujun |
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Description: 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 Platform: |
Size: 69632 |
Author:abdurusul |
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Description: 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 tasks in digital image processing. Detection of salient image regions is useful for applications like image segmentation, adaptive compression, and region-based image retrieval. This problem can be tackled by mapping the pixels into various feature spaces, which are subjected to various grouping algorithms It present a novel method to determine salient regions in images using low-level features of luminance and color. The method is fast, easy to implement and generates high quality saliency maps of the same size and resolution as the input image. Platform: |
Size: 1024 |
Author:shailesh kochra |
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Description: 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 images. 2 Select retrieval library path. Choose retrieval methods: based on color feature, shape-based features or characteristics based on color and shape. 4 Click the Start retrieve】 button to retrieve the results. Platform: |
Size: 1332224 |
Author:li |
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Description: 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 quite good. Platform: |
Size: 1609728 |
Author:wangyilin |
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Description: 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. These techniques are applied to get an image the image . They are not concerned with the various resolutions of the images, size and spatial color distribution. Hence all these methods are not appropriate to the art image retri . Moreover shape based retri s are useful only in the limited domain. The content and metadata based system gives images using an effective image retri technique. Many other image retri systems use global features like color, shape and texture. But the prior results say there are too many false positives while using those global features to search for similar images. Hence we give the new view of image retri system using both content and metadata -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. These techniques are applied to get an image the image . They are not concerned with the various resolutions of the images, size and spatial color distribution. Hence all these methods are not appropriate to the art image retri . Moreover shape based retri s are useful only in the limited domain. The content and metadata based system gives images using an effective image retri technique. Many other image retri systems use global features like color, shape and texture. But the prior results say there are too many false positives while using those global features to search for similar images. Hence we give the new view of image retri system using both content and metadata Platform: |
Size: 39936 |
Author:kilo |
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Description: % 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, a total of four matrices
The gray level of the image used is 256
% refer to image retrieval based on color space and texture features) Platform: |
Size: 1024 |
Author:火焰约定
|
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Search - Image Retrieval Color Features