Content Based image Retrieval is an important and fascinating point of the image database.
基于内容的图像检索是当前图像数据库领域的一个研究热点。
Color and shape are common features which were used in the Content Based Image Retrieval System.
颜色和形状都非基于外容的图像检索体解外常常当用的特征。
The traditional float vector based image feature is the base of content based image retrieval techniques.
传统的以浮点矢量形式表示的图像特征，是基于内容的图像检索技术的基础。
In this paper, constructing object description model in content based image retrieval system is focused on.
研究了基于内容的图像检索系统中的目标描述模型的建立方法。
The color spatial distribution density can provide the color spatial distribution information for CBIR(Content Based Image Retrieval).
在基于内容的图像检索中，颜色的空间分布密度能提供颜色在空间的分布信息。
In modern society, the development of the Content Based image Retrieval System getting faster and faster, it contains more and more images.
反在现代社会外，图像检索体解的收铺越来越快，体解外所包括的图像越来越长。
In content based image retrieval system, search engine retrieves the images similar standard to the Cey words query image according to a similarity measure.
在基于图像内容的图像检索系统中，搜索引擎检索图像类似于按照相似标准来查询图像。
Content based image retrieval (CBIR) has been an active research area, however, the achievements in image representation and similarity measurement are not satisfying.
基于内容的多媒体信息检索是当前世界的研究热点，然而在图像内容表示及其相似性度量这两个关键问题上取得的进展还不能令人满意。
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。
We analyzed the difficulties of traditional method of retrieval and introduced the highlights of content based image retrieval systems, its structure modules and general processing methods.
分析了传统的图象检索方法的困难，比较了基于内容的图象检索系统所具有的优点、系统结构及一般的处理方法。
Content based image retrieval is to perform the similarity retrieval according to the image features representing the image content, which may be extracted in the generic or specific domain.
基于内容的图像检索是根据描述图像视觉内容的特征向量进行相似性检索，其中图像视觉内容的提取可以是通用的，也可以是基于特定领域的。
Considering the fact of the ill fish image, the paper researched and presented the algorithm of content based image retrieval that was according to the represent shape, color or vein in image.
结合鱼病图像的实际，本文研究并实现了用形状特征、颜色特征和纹理特征分别进行基于内容的图像检索方法。
Based on image Processing and database Management System, Content Based image Retrieval (CBIR) is employed to obtain approximate results from image database, using the visual feature of images.
基于内容的图像检索技术是利用计算机图像处理和数据库管理系统，把图像的可视特征作为数据库检索的依据，对图像数据库进行近似检索。
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。
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。
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。
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。
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。
This paper presents the design and implementation of a content-based image retrieval system which acquires effective and efficient similar shape retrieval using a modified geometric hashing technique.
文中介绍了一个基于内容的图像检索系统的设计和实现，它利用改进的几何散列技术能够获得快速而且准确的相似形状检索。
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。
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。
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。
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。
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 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。
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。
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。
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。
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。
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。
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