image retrieval的例句大全

In this paper, support vector machines are trained for natural image classification. The resulting image class models are incorporated into image retrieval system, so that the users can search natural images by classes.

该文以自然图像领域为例，使用支持向量机（SVM）学习自然图像的类别，学习到的模型用于自然图像分类和检索.贫验结果和模拟象符合的较好。

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trademark image retrieval using shape features based on texture analysis

基于纹理分割的形状特征相似的商标检索技术

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In this paper a new image retrieval system is proposed, embed text information and image attributes inside the compressed images for their quickly retrieval.

本文提出一种新的图像检索系统，采用数据隐藏算法把图像的标注信息和特征信息嵌入压缩域图像中，用于快速检索。

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This paper is expanded around the application of visual attributes to content-based image retrieval and does the following research: First, this paper introduces the applications of image visual attributes in the various fields of image processing.

本文围绕视觉属性在图像检索中的应用进行了如下研究：（1）介绍了图像视觉属性在图像处理各个领域的应用情况，分析出属性在当前图像检索领域被广泛应用的趋势。

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Text-based image retrieval techniques, first manually extracting the image keywords used to describe the image contained in the content, and then use the database query technology through the text mode to retrieve the corresponding image.

基于文本的图像检索技术，首先以人工方式对图像提取关键字，用来描述图像包含的内容，然后利用数据库的查询技术通过文本方式来检索对应的图像。

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RAH: A Texture Based Image Retrieval Algorithm Based on the Histogram of Image Power Spectral

基于图像能量谱直方图的纹理检索算法RAH

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Texture Image Retrieval Based on Double Density Wavelet Transform

基于双密度小波变换的纹理图像检索

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Efficient technology of image retrieval can greatly help people obtain entertainment on Internet and enhance the quality of lives. Nowadays, textual retrieval performs well.

高效的图像检索技术能够极大地有助于人们在互联网上进行数字娱乐，提高人们的生活品质。

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Content-based image retrieval ( CBIR) is a hotspot of image retrieval at computer filed. It is different from traditional textual retrieval.

基于内容的图像检索是目前计算机图像检索研究的热点，它不同于传统的文本检索，因此将其应用于医学图像领域具有重要意义。

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Content-based image retrieval ( CBIR) system is different from traditional retrieval system based on text mode.

所谓基于内容的图像检索系统，具有与传统基于文本的检索系统完全不同的框架。

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Research of Necktie Pattern Retrieval Based on Image Retrieval

基于图像检索技术的领带花型检索的研究

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Study of Content-Based Image Retrieval Algorithm for Necktie Pattern

基于领带花形图像检索算法研究

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JPEG Image Retrieval Based on the Spatial Distribution of the DCT Coefficients

基于DCT系数空间分布的JPEG图像检索算法

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In order to provide an interactive way for users, this paper utilizes WPF structure to design and realize the sketch-based image retrieval system.

为了给用户提供方便的交互方式和将技术应用到实际中，本文采用WPF结构设计和开发了基于手绘草图的图像检索系统。

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In order to solve the problem, this thesis presents a novel user interactive image retrieval system.

为解决该问题，本文给出一种新的用户交互式图像检索系统。

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An image retrieval algorithm based on HSV color segment histograms

基于HSV分块颜色直方图的图像检索算法

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In this paper, we review the development of CBIR and discuss some main techniques of CBIR, including color index, shape index and texture index which are used in image retrieval. Typical commercial and experimental systems of content-based image retrieval are introduced.

综述了基于内容检索技术的进展，并对其主要方法如基于颜色、形状、纹理等图像检索技术进行了论述，介绍了几个典型的基于内容的图像检索系统。

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Experiments show that the improved coarseness has higher texture discriminability and better circumrotation invariance, and that the image retrieval result based on the improved coarseness is superior to that based on the previous coarseness.

实验表明，改进纹理粗糙度具有更强的纹理分辨能力和更好的旋转不变性，基于改进纹理粗糙度的图象检索结果优于基于原有纹理粗糙度的图象检索结果。

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Feature extraction is one of the elementary problems in the area of image retrieval. It is the key to the retrieval problems based not only on domain specific visual contents, general visual contents but also on semantic contents.

特征提取是图像检索研究的最基本的问题之一，无论是基于特定领域的视觉内容、基于通用视觉内容还是基于语义内容的图像检索，提取有效的鉴别特征是解决检索问题的关键。

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firstly, this paper presents the trademark image retrieval method based on distance distribution histogram.

首先，本文提出了基于距离分布直方图的商标图像检索方法。

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