基于形状和颜色内容及相关反馈的图像检索

Mussarat Yasmin, S. Mohsin
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引用次数: 4

摘要

在当今的数字通信时代,数字图像在表达、共享和解释信息方面的使用率越来越高。在处理数字图像时,经常需要根据图像的视觉内容搜索特定情况下的特定图像。根据内容检索图像是在庞大的数字图像库中检索特定图像的现代方法之一。随着万维网的日益普及,CBIR已广泛应用于大多数网站、软件和数据库系统。在过去的几年里,在这个领域进行了大量的研究,许多CBIR系统已经被提出、实施和使用。不同的CBIR系统有不同的基于内容的图像查找方法,因此它们具有不同的性能和精度度量。研究人员提出了一些非常聪明的技术来实现高效和鲁棒的基于内容的图像检索。在本研究中,目的是突出研究人员的努力,他们进行了一些杰出的工作,基于这些知识,我将提出新的基于内容的图像检索组合技术,专注于高性能和改进的相关性,并将为基于内容的智能图像检索提供概念证明。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Image Retrieval by Shape and Color Contents and Relevance Feedback
In the current era of digital communication, the use of digital images has grown high for expressing, sharing and interpreting information. While working with the digital images it is quite often that one needs to search for a specific image for a particular situation based on the visual contents of the image. Image retrieval by contents is one of the modern ways for searching huge digital image repositories for specific images. With the growing usage of World Wide Web CBIR is now very commonly used on most of the websites, software and database systems. In past years much of the research has been conducted in this domain and many CBIR systems have been proposed, implemented and being used. Different CBIR systems have different approaches to find images based on their contents and thus they have different performance and accuracy measures. There are some really smart techniques proposed by researchers for efficient and robust content based image retrieval. In this research, the aim is to highlight the efforts of researchers who conducted some brilliant work, based on this knowledge I will propose new combinational techniques for Content Based Image Retrieval focusing high performance and improved relevance and will provide proof of concept for intelligent content based image retrieval.
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