基于内容的图像检索

论述了基于内容的图像检索技术（CBIR）的新进展，提出了引入相关反馈机制、多种特征组合检索、图像聚类检索等三种改进其性能的方法，并通过实例论证了这些方法的有效性。

This paper mainly discusses the development of the CBIR in the digital library and puts forward three methods to improve the performance of CBIR system and demonstrates the effectiveness of relevant feedback technique , composite retrieval and the clustering technique by example .

如何有效准确地描述图像特征是基于内容的图像检索技术的一个核心问题。

Image feature representation is one of the key issues in CBIR .

基于内容的图像检索中SS-树索引的Java实现

Realization of the SS-tree Index in Content-Based Image Retrieval Using Java

基于内容的图像检索（ContentBasedImageRetrieval，CBIR）技术就是解决这一问题的关键技术之一。

Content based image retrieval ( CBIR ) is just one of key technologies for such a problem .

因此，基于内容的图像检索（Content-basedImageRetrieval，CBIR）已成为解决图像检索问题的研究热点。

So the content-based image retrieval ( CBIR ) has been widely researched .

距离度量学习及其在基于内容的图像检索（content-basedImageRetrieval，CBIR）上的应用研究。

Distance metric learning and its applications to content-based image retrieval ( CBIR ) .

基于内容的图像检索中SVM和Boosting方法集成应用

Ensemble application of SVM and Boosting in content-based image retrieval

基于内容的图像检索技术（CBIR，Content-basedImageRetrieval）是其中最基础、最重要的一个方向。

The Content-based Image Retrieval ( CBIR ) technology can exactly meet the needs mentioned above .

近年来，基于内容的图像检索（Content-basedImageRetrieval，CBIR）技术获得了蓬勃的发展。

Recently , the techniques of content-based image retrieval ( CBIR ) have been achieved great developments .

近年来，随着多媒体和网络技术的迅速发展，基于内容的图像检索技术（CBIR：Content-basedImageRetrieval）成为一个研究热点。

In recent years , with the rapid development of the technology of multimedia and network , Content-based image retrieval ( CBIR ) has been an active research topic .

利用Gabor滤波器的基于内容的图像检索

Content-based Image Retrieval Using Gabor Filters

基于内容的图像检索CBIR（Content-basedImageRetrieval）是多媒体信息处理的研究热点之一，有着广泛的应用背景。

Content-based image retrieval ( CBIR ) is a hotspot of research in multimedia information processing field , and has capacious developed foreground .

因此，基于内容的图像检索（CBIR）技术应运而生，便逐渐成为当前的一个热门研究课题。

Therefore , the Content-based Image Retrieval ( CBIR ) technique emerged .

为了克服传统检索方法的局限性，基于内容的图像检索CBIR（ContentBasedImageRetrieval）技术应运而生，并成为图像领域研究的热点问题之一。

In order to overcome the limitation of the traditional searching method , the CBIR ( Content-Based Image Retrieval ) has become one of the hot research areas in image domain .

将基于内容的图像检索应用到P2P网络中，提出了一种基于类簇的P2P网络信息搜索机制。

The content-based image retrieval system was introduced into P2P network and a novel search model based on " cluster clustering " was presented .

本文综合考虑了基于内容的图像检索及SAR图像的特点提出了基于高斯混合模型分类的SAR图像检索方法。

This paper considers the characteristic of content-based image retrieval ( CBIR ) and SAR image together , proposing a method of SAR image retrieval .

提出了基于内容的图像检索技术CBIR应用于数字图书馆中多媒体信息检索的一些方法。

CBIR applies to digital library searching Multimedia information .

实验结果表明，提出的可变k近邻LLE数据降维方法在基于内容的图像检索中有较高的检索准确率。

Experiment shows that the proposed VK-LLE method can achieve higher precision rate in content based image retrieval problem .

ISODATA高效迭代算法在基于内容的图像检索中的应用

Application of ISODATA Iterative Algorithm Based on Image Search of the Content

因此，基于内容的图像检索（CBIR）已经成为当前国内外研究的热点。

So content-based image retrieval ( CBIR ) is now the study hot-point in the world .

基于内容的图像检索（CBIR）技术是当前研究的热点问题。

At present , Content-Based Image Retrieval ( CBIR ) is becoming a hot research topic .

基于内容的图像检索（CBIR，Content-basedImageRetrieval）是利用图像内容实现图像检索的一项综合性技术，是指根据图像内容特征以及特征组合，从图像库中查找含有特定内容的图像。

Content-Based Image Retrieval ( CBIR ) is an integrated technique , which retrieves image from image database on the basis of the content feature of the image .

基于内容的图像检索与MPEG-7

Content-Based Image Retrieval and MPEG-7

基于内容的图像检索（CBIRContent-basedImageRetrieval）的目的在于通过某种特定的方法在数据库中寻找出满足一定人类视觉特征的图像的过程。

The goal of Based on content image retrieval ( CBIR Content-Based Image Retrieval ) lies in through some specific method seeks a process satisfies the human vision characteristic of image .

本文研究的多媒体图像主要包括图像、图形和文字这些内容。基于内容的图像检索（CBIR，Content-basedImageRetrieval）是一种利用图像的视觉特征（颜色、纹理、形状等）进行图像检索的技术。

Content-Based Image Retrieval ( CBIR ) is a kind of technique for retrieval images on the basis of automatically extracting visual features such as color , texture , and shape etc.

在MPEG-7标准下研究图像的特征提取技术可以增强基于内容的图像检索系统的通用性。

Feature extraction techniques which based on MPEG-7 standard can enhance the interoperability of content-based image retrieval systems .

特征提取是基于内容的图像检索（ContentBasedImageRetrieval，CBIR）、图像分类等计算机视觉的关键环节之一，准确地表示出图像涵盖的信息是至关重要的。

Feature extraction is one of the important aspects in computer vision , which consists of CBIR ( Content Based Image Retrieval , CBIR ), image classification and so on . It is significant to extract image information exactly .

随着医学图像数据量迅速膨胀，基于内容的图像检索（CBIR，Content-basedImageRetrieval）技术在医学辅助诊断中越来越得到重视。

With the rapid increase of medical image amount , the research of CBIR ( Content-based image retrieval ) and its application on CAD ( Computer-Assistant Diagnosis ) receive more and more concerns .

随着多媒体和Internet技术的快速发展，基于内容的图像检索已经成为图像处理和计算机视觉领域的研究热点，基于内容的图像检索具有广阔的应用前景和重要的学术研究价值。

Along with the speedy development of the multimedia and Internet techniques , content-based image retrieval ( CBIR ) has become one of the hot topics on image processing and computer vision , content-based image retrieval has broad application prospects and important academic value .

因此，如何高效的管理和检索现代大规模的图像数据库，已成为目前的一个研究热点，基于内容的图像检索（Content-basedImageRetrieval，CBIR）技术应运而生。

So , it has become a research hotspot how to effectively manage and retrieve large scale image database , the content-based image retrieval ( Content-based Image Retrieval , CBIR ) technology came into being .