Description: 基于内容的图像检索中的一些关键环节：特征提取：颜色直方图；纹理特征等
相似度：马氏距离，欧氏距离等
相关反馈：机器学习方法，如SVM，神经网络等
检索与分类：两个很相似的样本距离很小，虽然两个不相似的样本距离未必很大-content-based image retrieval of some of the key issues : Feature Extraction : color histogram; Texture characteristics of similarity : Mahalanobis distance, the Euclidean distance relevance feedback : machine learning methods, such as SVM. Neural network search and classification : two very similar samples from the small, although the two are similar to the samples may not be much distance Platform: |
Size: 160149 |
Author:耿上 |
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Description: 基于内容的图像检索中的一些关键环节：特征提取：颜色直方图；纹理特征等
相似度：马氏距离，欧氏距离等
相关反馈：机器学习方法，如SVM，神经网络等
检索与分类：两个很相似的样本距离很小，虽然两个不相似的样本距离未必很大-content-based image retrieval of some of the key issues : Feature Extraction : color histogram; Texture characteristics of similarity : Mahalanobis distance, the Euclidean distance relevance feedback : machine learning methods, such as SVM. Neural network search and classification : two very similar samples from the small, although the two are similar to the samples may not be much distance Platform: |
Size: 159744 |
Author:耿上 |
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Description: 基于内容的图像检索示例代码，给定一幅原图像，在图像数据库中根据与原图像之间相似度的大小，搜索与原图像最接近的若干幅图像。本程序相似度主要以两幅图像之间直方图的距离为衡量标准，对此内容感兴趣的同学可以在此基础上加入更多的相似度判别算法。-Content-Based Image Retrieval sample code, given a piece of the original image, the image database in accordance with the similarity between the original image size, image search and the original number of the nearest images. This procedure mainly on the similarity between two images, the distance histogram for the measure, this content of interest to students on the basis of similarity to include more discriminant algorithm. Platform: |
Size: 43008 |
Author:张柳新 |
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Description: 基于图像内容的视觉相似搜索引擎,自动分析图像中的颜色、纹理、形状、空间特征等
作为搜索的关键数据，通过特定算法搜索相似的图片。-The visual image content-based similarity search engine, automatic analysis of images in color, texture, shape, spatial characteristics of the critical data as a search through a particular search algorithm similar to the picture. Platform: |
Size: 891904 |
Author:birch |
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Description: 基于内容的图像检索（cbir）
可以对图像库进行相似度计算并给出图像搜索的结果-Content-Based Image Retrieval (cbir) image library can be calculated and given the similarity of image search results Platform: |
Size: 598016 |
Author:张史 |
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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: |
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Author:qichao |
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Description: 实现“基于互信息量”进行关键帧提取的具体算法，该算法以帧间的互信息量来衡量两帧图像内容的相似性，可以对具体镜头按其特点自动提取出一或多个关键帧。-To achieve " Based on mutual information" to a specific key-frame extraction algorithm in order to frames to measure the two mutual information similarity of image content can be according to the specific characteristics of the lens automatically extracted one or more of the key-frame . Platform: |
Size: 4141056 |
Author:feilong |
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Description: Weintroduceanewsimilaritymeasurebetweendatapointssuited
respecttoclustercentroids),shareswiththepreviousapproachthe
for clustering and classi?cation on smooth manifolds. The pro-
sameproblemsin itsoptimization formulation.
posed measure is constructed from a dual rooted graph diffusion
Recently, the focus of attention in unsupervised learning has
over the feature vector space, obtained by growing dual rooted
turned to spectral clustering methods due to its many successes
minimum spanning trees (MST) between data points. This diffu-
[1]. These methods use the spectral content of a similarity ma-
sionmodelforpairwiseaf?nitiesnaturallyac Platform: |
Size: 204800 |
Author:quinquindavid |
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Description: Along with investigating similarity metrics between audio
material, the topic of robust matching of pairs of audio content
has gained wide interest recently. In particular, if this matching
process is carried out using a compact representation of the audio
content ("audio fingerprint"), it is possible to identify unknown
audio material by means of matching it to a database with the
fingerprints of registered works. This paper presents a system for
reliable, fast and robust identification of audio material which can
be run on the resources provided by today s standard computing
platforms. The system is based on a general pattern recognition
paradigm and exploits low level signal features standardized
within the MPEG-7 framework, thus enabling interoperability on
a world-wide scale. Platform: |
Size: 116736 |
Author:ahmed |
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Description: E-mail spam has become an epidemic problem that
can negatively affect the usability of electronic mail as
a communication means. Besides wasting users’ time
and effort to scan and delete the massive amount of
junk e-mails received it consumes network bandwidth
and storage space, slows down e-mail servers, and
provides a medium to distribute harmful and/or
offensive content.-E-mail spam has become an epidemic problem that
can negatively affect the usability of electronic mail as
a communication means. Besides wasting users’ time
and effort to scan and delete the massive amount of
junk e-mails received it consumes network bandwidth
and storage space, slows down e-mail servers, and
provides a medium to distribute harmful and/or
offensive content. Platform: |
Size: 1175552 |
Author:Prathmesh |
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Description: 基于图像检索的matlab代码，基于内容的图像检索中的一些关键环节：特征提取：颜色直方图；纹理特征等 相似度：马氏距离，欧氏距离等 相关反馈：机器学习方法，如SVM，神经网络等 检索与分类：两个很相似的样本距离很小，虽然两个不相似的样本距离未必很大-content-based image retrieval of some of the key issues : Feature Extraction : color histogram Texture characteristics of similarity : Mahalanobis distance, the Euclidean distance relevance feedback : machine learning methods, such as SVM. Neural network search and classification : two very similar samples from the small, although the two are similar to the samples may not be much distance Platform: |
Size: 164864 |
Author:EmilyFu |
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Description: 一个小型的文档推荐系统，改推荐系统主要基于内容的方法进行推荐。-An smart file recommend system which is based on content Similarity。 Platform: |
Size: 6360064 |
Author:Kuan Zhang |
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Description: cbirIn this paper, we present a new framework for effective content-based image retrieval (CBIR) using rectangular segmentation. In image segmentation, speed is more important than accuracy in CBIR. We propose a new rectangular approximate image segmentation to solve the problem. We also develop a significance function to reflect the importance of different position in image, and improve the segmentation and retrieval performance. Finally, we present a similarity measure between images with multi-objects. Experimental results show that the proposed method is more efficient and achieves higher precision on image retrieval of a large dataset. Platform: |
Size: 4096 |
Author:zainab |
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Description: 基于内容的图像检索（Content-based Image Retrieval，简称CBIR）技术被提出。这一技术的出现提高了图像检索的准确性，它通过提取图像本身的内在客观特征如颜色、纹理、形状、布局等关系，并比较这些视觉特征间的相似性，自动搜索出符合用户要求的图像。-Content-based image retrieval (Content-based Image Retrieval, referred to as CBIR) techniques have been proposed. The emergence of this technology to improve the accuracy of the image retrieval, intrinsic objective characteristics by extracting an image itself such as color, texture, shape, layout relations, and compare the similarity between the visual characteristics, automatically searched out in accordance with the user requirements images. Platform: |
Size: 2048 |
Author:周佳森 |
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Description: 随着遥感图像数量的急剧增加, 基于内容的遥感图像检索系统逐渐成为了一个研究热点。系统地介
绍了该领域各个方面研究的现状。首先给出了遥感图像内容检索系统的基本结构和查询策略。其次,结合遥
感图像的特点,着重介绍了基于纹理、形状、结构特征相似性比较等方面的内容, 针对这些方面的研究所存在
的问题提出了见解, 介绍了所研究成果,并对今后的工作进行了展望。-The content- basedretrieval (CBR) systemfor remotesensing images(RSI) hasbeena hot researchareare-cently withanincreasing huge amount of imagedata generatedduring the two decades
. The present situationof eachre-search aspect in this area is introduced. Considering the features of remote sensing images
,
the structure and query
strategiesof the CBRsystemfor RSI arediscussed. Similarity comparisonof the texture, shape andtopography are dis-cussed. Suggestions arepresentedto solve the existing problemsinthisfield. Some opinions about problemsexisting in
this area are presentedandthe future development is described. Platform: |
Size: 176128 |
Author:li |
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Description: 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 similarity
function for the representation short- and long-term procedures
for learning. We identify a series of requirements for each of the
sub-areas, e.g. optimality, invariance, perceptual relevance, computational
tractability, and point out various approaches proposed
to satisfy them. Several open problems are also identified-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 similarity
function for the representation short- and long-term procedures
for learning. We identify a series of requirements for each of the
sub-areas, e.g. optimality, invariance, perceptual relevance, computational
tractability, and point out various approaches proposed
to satisfy them. Several open problems are also identified Platform: |
Size: 43008 |
Author:silkan |
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Description: 基于图像内容中的颜色和纹理特征能够实现对大量图片快速准确进行相似度检测(Based on the color and texture features of the image content, similarity detection can be carried out quickly and accurately for a large number of images) Platform: |
Size: 5419008 |
Author:御心home |
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Search - content similarity