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提出了一种基于主颜色、聚类索引表的彩色图像检索算法。应用MPEG-7视觉内容描述对彩色图像进行量化处理,选取图像的主颜色及其所占百分率作为颜色特征,根据主颜色组合建立聚类索引数据库。利用上述主颜色特征计算图像间的相似度,利用聚类索引表对图像进行聚类和快速检索。实验表明,该算法能够准确和高效地检索出用户所需的彩色图像,具有较快的检索速度。 相似文献
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一种有效的支持海量图像数据库QBE查询的聚类索引算法 总被引:2,自引:0,他引:2
对海量图像数据进行基于内容的查询与检索有赖于高效的索引和检索机制。因此,如何将海量图像数据进行合理的分类,人而建立相应的索引机制就成为了一个亟待解决的问题。本文提出了一种有效的支持海量图像数据库QBE查询的聚类索引算法。实验在1万多幅的图像数据库上进行了反复测试,结果表明该算法可以极大地提高检索效率。 相似文献
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基于色彩主特征的快速图像检索 总被引:2,自引:0,他引:2
提出了一种新颖而又简单直观的图像索引机制。这种方法通过统计图像数据库的低层像素特征,用中值切割法构建索引树,把自然景物图像数据库分成易于描述的不同视觉主题,并籍此来进行高效的图像检索。索引树的构建有别于传统的完全基于数值本身的聚类方法,因而聚类结果视觉含义更明显。本文以颜色主题为例实现了此方法,并通过实验论证了方法的高效和快速。图像索引码以二进制形式给出,因而所需存储空间也极小。 相似文献
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逐维聚类的相似度索引算法 总被引:5,自引:0,他引:5
随着多媒体信息技术的迅速发展,多维度索引技术在图像、视频等可视信息的存储、检索方面成为一个重要的研究领域,针对“维数危机”难题,提出逐维聚类相似度索引算法,该算法根据数据集的分布特性,对特征矢量的每一维进行聚类,算法在实现检索时可以逐步滤除与查询矢量不相似的数据集,缩小检索范围,进而提高了检索速度,实验结果表明,逐维聚类算法适用于基于相似度的高维数据矢量检索和查询,是一种简单、灵活的索引结构。 相似文献
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基于内容的多媒体数据查询和检索 总被引:27,自引:4,他引:27
多媒体数据具有可表现的视觉和听觉特性,而难于用符号形式来描述。本文介绍基于内容的对多媒体数据进行查询和检索的概念和方法,描述查询和检索的一般系统结构、用户查询类型、索引/过滤机制,以及视频的检索和浏览,并给出基于内容检索研究中值得探索的几个主要问题。 相似文献
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利用聚类算法提高基于内容的图像检索准确率 总被引:3,自引:0,他引:3
给出了一种基于内容的图像检索算法,该算法使用了图像的颜色直方图作为图像的检索特征,并且利用了K均值聚类算法以及用户相关反馈技术来提高检索的准确率。 相似文献
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图像局部不变特征已经成功地应用在计算机视觉当中的许多领域,而如何快速有效地匹配高维图像局部特征向量是解决这类问题的关键步骤。提出了一种新的基于子向量距离索引的高维特征向量匹配算法,将高维空间中最近邻搜索问题转化为一维索引值的查找和局部搜索问题,在保证较高的搜索精度的同时大大提高了搜索速度。大量的图像匹配和图像检索实验验证了该算法的有效性。 相似文献
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James Ze Wang Gio Wiederhold Oscar Firschein Sha Xin Wei 《International Journal on Digital Libraries》1998,1(4):311-328
This paper describes WBIIS (Wavelet-Based Image Indexing and Searching), a new image indexing and retrieval algorithm with
partial sketch image searching capability for large image databases. The algorithm characterizes the color variations over
the spatial extent of the image in a manner that provides semantically meaningful image comparisons. The indexing algorithm
applies a Daubechies' wavelet transform for each of the three opponent color components. The wavelet coefficients in the lowest
few frequency bands, and their variances, are stored as feature vectors. To speed up retrieval, a two-step procedure is used
that first does a crude selection based on the variances, and then refines the search by performing a feature vector match
between the selected images and the query. For better accuracy in searching, two-level multiresolution matching may also be
used. Masks are used for partial-sketch queries. This technique performs much better in capturing coherence of image, object
granularity, local color/texture, and bias avoidance than traditional color layout algorithms. WBIIS is much faster and more
accurate than traditional algorithms. When tested on a database of more than 10 000 general-purpose images, the best 100 matches
were found in 3.3 seconds. 相似文献
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As the majority of content-based image retrieval systems operate on full images in pixel domain, decompression is a prerequisite for the retrieval of compressed images. To provide a possible on-line indexing and retrieval technique for those jpg image files, we propose a novel pseudo-pixel extraction algorithm to bridge the gap between the existing image indexing technology, developed in the pixel domain, and the fact that an increasing number of images stored on the Web are already compressed by JPEG at the source. Further, we describe our Web-based image retrieval system, WEBimager, by using the proposed algorithm to provide a prototype visual information system toward automatic management, indexing, and retrieval of compressed images available on the Internet. This provides users with efficient tools to search the Web for compressed images and establish a database or a collection of special images to their interests. Experiments using texture- and colour-based indexing techniques support the idea that the proposed algorithm achieves significantly better results in terms of computing cost than their full decompression or partial decompression counterparts. This technology will help control the explosion of media-rich content by offering users a powerful automated image indexing and retrieval tool for compressed images on the Web.J. Jiang: Contacting author 相似文献
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Amir Masud Eftekhari-MoghadamAuthor Vitae Jamshid ShanbehzadehAuthor Vitae 《Pattern recognition》2003,36(11):2635-2647
Increased amount of visual data in several applications necessitates content-based image retrieval. Since most of visual data is stored in compressed form, it is crucial to develop indexing techniques for searching images based on their content in compressed form. Therefore, it is desirable to explore image compression techniques with capability of describing image content in compressed form. Vector Quantization (VQ) is a compression scheme that exploits intra-block correlation and image correlation reflects image content, hence VQ is a suitable compression technique for compressed domain image retrieval.This paper introduces a novel indexing scheme for compressed domain image databases based on indices generated from IC-VQ. The proposed scheme extracts image features based on relationship between indices of IC-VQ compressed images. This relationship detects contiguous regions of compressed image based on inter- and intra-block correlation. Experimental results show effectiveness superiority of the new scheme compared to VQ and color-based schemes. 相似文献
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基于P2P的隐含语义索引模型的研究 总被引:4,自引:2,他引:2
P2P作为一种新型的网络结构正受到越来越多的关注。目前在大多数P2P网络中的信息检索方法都是依据关键词匹配,通过查询请求与信息标识之间的简单匹配关系来获得查询结果。但是关键词匹配会产生很多用户不需要的结果。隐含语义索引是基于文本语义的检索模型。为提高系统的查准率,扩展在P2P下的查询方式,本文提出了在P2P网络中引入隐含语义索引模型进行信息检索,并模拟实现了一个基于P2P网络的隐含语义索引模型的试验平台。 相似文献
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针对不同时间尺度视频间的匹配问题,如人为再编辑(快进、慢放等)视频与原始视频间的匹配以及不同帧率视频间的检索等,提出了一种基于动态时间规划的最优匹配算法。在子片段的基础上进行视频相似性匹配,通过极小化两段视频的整体距离建立视频之间的子片段对应关系,引入搜索门限值,将全局搜索转变为在门限区域内的局部搜索,保持视频内部各子片段之间的时序关系并能处理非线性偏移。该算法能够成功地匹配不同时间尺度的相似视频,并能实现海量视频的快速检索。实验结果证明了该算法比传统的基于视觉相似性的视频片段检索算法更快速有效。 相似文献