基于内容的图像检索系统中图像特征的合成与匹配

Ranjana Battur, N. Jagadisha
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引用次数: 0

摘要

基于内容的图像检索是信息数据分析中的一个重要概念。我们生活在信息时代。在现代数字信息技术成像世界中,这在从国防到研究领域的不同部门中发挥着主导作用。基于内容的图像检索,又称按图像内容查询,是计算机视觉技术在图像检索问题中的应用,即在大型数据库中搜索数字图像或文本事项的问题。由于存储和网络技术的迅猛发展,数字图像的使用在过去十年中得到了极大的增长。这些技术变革使得专业用户能够使用、存储和操作远程存储的图像。信息检索(Information Retrieval, IR)处理基于用户输入的相关文档或图像的定位和检索,例如关键字或来自存储库的查询示例。这促使我们开始着手对cir概念的研究工作。因此,为了阐明所选择的研究课题,我们利用AI, ML和模糊逻辑方案的概念对基于内容的图像检索系统中的图像特征合成和匹配进行了广泛的研究,可用于提高检索系统在CBIRs中的性能。一个简短的调查,即对基于内容的图像检索领域所选择的研究领域的深入了解,并以广泛的文献综述的形式介绍了全球各种研究人员所做的工作。对他们所做的工作进行了研究,发现了不足之处,并对问题进行了定义,提出了四个目标:1 .研究进化计算在生成图像复合算子向量中的有效性,降低特征维数,提高检索性能;O2 -图像层的构建
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Image Feature Synthesis and Matching in Content-Based Image Retrieval System – A Review
One of the important concepts in information & data analytics is the content-based image retrieval process. We are living in the information age. In the modern-day digital information technology imaging world, this is playing a predominant role in different sectors ranging from defense to research fields. Content-based image retrieval, also known as query by image content is the application of computer vision techniques to the image retrieval problem, that is, the problem of searching for digital images or textual matters in large databases. The usage of digital images has been increased enormously from the last decade due to the drastic growth in storage & network technology. These technological changes have led professional users to use, store and manipulate remotely stored images. Information Retrieval (IR) deals with the location and retrieval of related documents or images based on user inputs such as keywords or examples as a query from the repository. This has motivated us to take up the research work on the CBIR concepts. Hence, to throw light into this chosen research topic, we are carrying out extensive research on the image feature synthesis and matching in content-based image retrieval systems using the concepts of AI, ML & Fuzzy Logic schemes, which could be used to improve the retrieval system's performance in CBIRs. A brief survey, i.e., an insight into the chosen research area in the field of content-based image retrievals was made & the same is being presented w.r.t. the work done by various researchers across the globe in the form of an extensive literature review. The work done by them was studied, lacunas observed & the problem was defined with a couple of good objectives to be solved four objectives were proposed as O1 - Investigation of the effectiveness of evolutionary computation in generating composite operator vectors for image, so that feature dimensionality is reduced to improve retrieval performances; O2 - Construction of the image-leve
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