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。
Based on the requirement of image query, the paper designs a framework of Content-Based image Retrieval system (CBIR), which possesses more functions than all kinds of existing CBIR systems.
依据当前对图象查询的要求，本文设计了一套完整的基于内容的图象信息检索系统，该系统较以往的各种系统，功能更加全面。
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。
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。
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。
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。
This article mainly introduces the design and optimized project of the Automatic Retrieval system based on image content.
该文主要介绍一种基于图像的外观专利自动检索系统的设计与优化方案。
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。
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。
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。
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。
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。
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。
A content-based medical image retrieval database system was introduced.
介绍了一个基于图像内容检索的医学图像数据库系统。
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。
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。
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 same time, it raise a new structure of system of content based image indexing and retrieval which can adapt oneself for adding successful semantic users did to semantic database.
同时提出一种基于内容的图像标引与检索系统结构，能自适应的在图像语义库中添加较为成功的语义表述。
The same time, it raise a new structure of system of content based image indexing and retrieval which can adapt oneself for adding successful semantic users did to semantic database.
同时提出一种基于内容的图像标引与检索系统结构，能自适应的在图像语义库中添加较为成功的语义表述。
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