In content-based image retrieval, color features are widely used.
在基于内容的图像检索中，颜色特征已得到广泛应用。
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。
Color histogram is the most usually used method of content-based image retrieval.
颜色直方图法是基于内容的图像检索系统通常采用的方法。
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。
Firstly, the basic theory and frame of content-based image retrieval technology are introduced.
首先对基于内容图像检索技术的基本原理和框架进行了概要介绍。
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。
At present, the content-based image retrieval technology becomes the mainstream of image retrieval.
目前，基于内容的图像检索技术成为图像检索的主流。
Through testing, we can see that these methods for content-based image retrieval have very good results.
通过试验可以看出，以上方法用基于内容的图像检索有很好的效果。
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。
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。
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。
Efficient indexing schemes for high-dimensional data are important for Content-Based Image Retrieval, with theoretical and applicable value as result.
有效的高维索引机制是基于内容的图像检索的关键技术，具有重要的理论意义和应用价值。
Finally, based on the key technologies of content-based image retrieval, a development example of content-based animation image retrieval was presented.
最后根据对基于内容图像检索关键技术的研究与分析，本文给出了一个基于内容的动漫图像检索系统的开发实例。
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。
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。
In this paper, a novel system for content-based image retrieval is designed and created, which combines image semantics based on a multi-level model for image description.
该系统利用了一个多级图像描述模型将语义特征结合到图像检索技术中。
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。
By analyzing the character of necktie pattern and studying image retrieval algorithm, an approach to content-based image retrieval for necktie pattern is proposed in this paper.
针对领带花形图像的具体特征，研究了适用于该类图像的检索算法。
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。
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。
The key technologies of content-based image retrieval (CBIR) system contain a lot of aspects. The most important point is how to represent multimedia content accurately and completely.
基于内容的图像检索系统涉及许多方面关键技术，如何准确有效的表示图像内容是其中的核心问题。
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。
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。
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