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随着计算机技术和国际互联网的飞速发展，包括图像在内的各种多媒体数据的数量正以惊人的速度增长，人们很容易在多媒体信息海洋中迷失方向，如何从中有效地检索有用信息是一个很关键和迫切的问题。本文回顾了图像检索技术的发展状况，阐述了基于内容的图像检索的关键技术，结合认知心理学模型和智能科学技术，重点探讨了未来图像检索的发展方向和技术路线。 -with computer technology and the Internet's rapid development, include images o
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基于图像内容的多维特征检索技术，主要利用图像的形状特征提取-Retrieval technique based on multi-dimensional characteristics of the image content, the main use of the shape of the image feature extraction
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Background of Content Based Image Retrieval(CBIR)
Analysis of Previous Work
Results of Existing Methods
Scalable Image Indexing and Retrieval
Proposed Indexing System(overview)
wavelet transform and HSL color conversion
Feature Space(Ener
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Nowadays, Content-Based Image Retrieval (CBIR) is the
mainstay of image retrieval systems. To understand the query
semantics and users expectations so as to communicate faithful
results in terms of accuracy, Relevance Feedback (RF) was
incorp
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In the current decade, we are witnessing a great interest in Content Based Image Retrieval (CBIR) together with a wealth of promising technologies, paved for a large number of new mechanisms and systems. In terms of mechanisms, a strong trend towards
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是一篇涉及多篇文章的关于图像检索的很好的综述-Is an involving multiple articles a good overview on image retri
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We review recent advances in image retri . The two fundamental
components of a retri system, representation and learning,
are analyzed. Each component is decomposed into its constituent
building blocks: features, feature representation, and sim
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This paper provides a comprehensive survey of the technical achievements in the
research area of image retri , especially content-based image retri , an area that
has been so active and prosperous in the past few years. The survey includes 100+
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