Image retrieval algorithms is the core of content-based image retrieval.
基于内容的图像检索的核心就是图像检索算法。
Content-based image retrieval, belong to the one research area of the image analysis.
基于内容的图像检索，属于图像分析的一个研究领域。
In recent years, the content-based image retrieval (CBIR) system is a hot research topic.
近年来，基于内容的图像检索系统(CBIR)是一个热门的研究话题。
The evaluation of texture similarity is very important in content-based image retrieval systems.
纹理相似性研究是基于内容检索研究中的一个重要组成部分。
The retrieval technique of content-based image database is a focus of query technology studying nowadays.
基于内容的图像数据库检索技术是当今的一个研究热点。
In this basis, the relevance feedback technology and relevance feedback model of content-based image retrieval.
在此基础上，引入基于内容的图像相关性反馈技术及相关性反馈模型。
Shape feature extraction and description are one of important research topics in content-based image retrieval.
形状特征提取和表示是基于内容图像检索的重要研究内容之一。
A novel automatic image annotation approach is proposed to bridge the semantic gap of content-based image retrieval.
针对图像检索中的语义鸿沟问题，提出了一种新颖的自动图像标注方法。
To access these image databases automatically and on demand requires the system of content-based image retrieval (CBIR).
实现基于内容的图象检索系统的关键问题是实现图象的语义分割。
Therefore, content-based image retrieval techniques have emerged, and it become hot in the field of image retrieval research.
因此，基于内容的图像检索技术就应运而生，并逐渐地成为图像检索领域的研究热点。
Fractal coding has been proved useful for image compression, and it is also proved effective for content-based image retrieval.
分形编码在图像压缩方面取得了很好的效果，同时也能够用于基于内容的图像检索。
The results indicate that the Content-based image retrieval method offers distinct advantages over some other image retrieval methods.
实验结果表明这种基于图象内容的检索方法，较方便和准确地达到了图象检索之目的。
Visional feature extraction, high dimensional indexing mechanism and relevance feedback are three important issues in content-based image retrieval.
低层视觉特征提取、高维数据索引机制和相关反馈方法是面向大规模图像库基于内容检索的三个关键问题。
This paper presents a color images region growing method based on online learning algorithm, which is used for content-based image retrieval systems.
论文阐述了一种基于在线学习算法的彩色图像区域增长法，用于解决基于内容的图像检索系统。
The Content-based image retrieval technique search the image in the image library by the content features. The result is similar to the target image.
基于内容的图像检索技术依据图像的画面内容特征来检索图像库中与目标图像相似的图像。
Experimental results indicate that algorithm design is feasible and good for the improvement of the accuracy of the retrieving rate to content-based image.
实验结果表明了该检索算法设计的可行性和对基于内容的图像检索准确率的提高。
This paper introduces the basic theory, retrieval mode and critical technology of content-based image retrieval and illustrates some advanced image retrieval systems.
本文介绍了基于内容图像检索的基本原理、检索方式和关键技术，并列举了几种较为先进的图像检索系统。
Two effective ways has been proposed to solve the problem : one is content-based image retrieval(CBIR) technique which search target images by low-level content feature.
基于内容的图像检索技术和基于语义的图像检索技术正是解决这一问题的有效途径。
At first, we introduce the current research situation of CBIR (Content-based image retrieval) both at home and abroad, basic theories, inquiry ways and application fields.
首先介绍了国内外基于内容的图象检索系统的研究现状，基本原理，查询方式以及应用领域。
This paper introduces the definition of the content-based image retrieval and the visual description tools of MPEG-7, and analyzes the application of the feature descriptor.
介绍了基于内容的图像检索的定义以及MPEG - 7中的视觉描述工具，分析了特征描述符的应用。
In content-based image retrieval systems, the inconsistency between image low-level features and the concept of high-level expressed by images lead to system semantic gap problem.
在基于内容的图像检索系统中，图像低层特征和图像所表达高层概念之间的不一致性导致系统出现语义鸿沟问题。
The retrieval technique of content-based image database is a focus of study nowadays, many institutes being engaged in this project have obtained some achievements home and aboard.
基于内容的图象数据库检索技术是当今的一个研究热点，国内外许多研究机构都在从事这一课题的研究，并取得了一定的研究成果。
Finally, a content-based image browse and retrieval system are designed to certify its validity and correctness, and the demonstrations of systematic operation result are provided.
最后设计出基于内容的图像浏览与检索系统以验证其有效性和正确性，并给出了系统运行效果示例。
Some experiments show that in the image database, which has joined the computer graphics and the real photos together, the content-based image retrieval will lose much of its accuracy.
使用区分真实照片与人工图片的算法进行图像的预分类与识别，对于提高基于内容的图像和影片检索的成功率有着较大的现实意义。
This paper focuses on the relevance feedback techniques in content based image retrieval and try to make this paper helpful for research and application of content-based image retrieval.
本文主要针对基于内容的图像检索中的相关反馈技术展开研究，希望通过本文的工作能够对基于内容图像检索领域的研究和应用有所帮助。
It presents the model and feature of content-based image retrieval system, and then discusses some methods of feature abstraction and similarity measurement based on color, texture and shape.
首先叙述了基于内容的图像检索的系统模型和特点，接着针对颜色、纹理和形状进行了概率特征提取、相似度量等的进一步具体分析讨论。
Finally, the technical implementation of our content-based image browse and retrieval test system, as well as some key components in building such a test system, is also covered in great detail.
最后通过完成一个基于内容的图像检索和浏览的实验系统设计与实现，讨论图像检索的具体实现过程，以及检索中需要用到的技术和可能遇到的问题。
Introduces color feature extraction and matching algorithms in content-based image retrieval, such as weighted Euclidean-distance, weighted centre distance, histogram intersection algorithm, etc.
介绍了基于内容图像检索中多种颜色的特征提取和匹配算法，以及加权欧几里得距离、中心距的加权距离、直方图交集算法等。
The retrieval technique of content-based image database is a focus of query technology studying nowadays, many institutes being engaged in this project have obtained some achievements home and abroad.
基于内容的图像数据库检索技术是当今的一个研究热点，国内外的许多研究机构都在从事这一课题的研究，并取得了一定的研究成果。
The retrieval technique of content-based image database is a focus of query technology studying nowadays, many institutes being engaged in this project have obtained some achievements home and abroad.
基于内容的图像数据库检索技术是当今的一个研究热点，国内外的许多研究机构都在从事这一课题的研究，并取得了一定的研究成果。
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