精品文档---下载后可任意编辑WEB 图像排序与互摘要的开题报告摘 要：随着互联网技术的持续进展，网络上存在着海量的图像数据，如何从这些数据中高效快速地找到目标图像，成为了普遍关注的问题。本文主要讨论 WEB 图像排序与互摘要算法，旨在通过对图像进行高效排序和摘要，方便用户快速地访问和浏览目标图像。本文首先介绍了当前主流的图像检索算法和 WEB 图像检索系统，分析了它们的优缺点和存在的问题，并提出了图像排序和互摘要算法的讨论意义和应用价值。其次，针对图像排序和互摘要两个问题，本文提出了具体的解决方案。其中，图像排序算法引入了多个权重因素，并利用遗传算法进行优化，实现了对 WEB 图像的高效排序。互摘要算法则通过对多个 WEB 图像进行综合分析，提取出其中的关键信息，形成互摘要，帮助用户快速定位目标图像。最后，本文对图像排序和互摘要算法进行了实验验证，并分析了实验结果。实验结果表明，本文提出的算法具有较高的效率和准确率，能够实现 WEB 图像的高效排序和互摘要，为用户提供了更加便捷的图像检索方式。关键词：WEB 图像；排序算法；互摘要算法；遗传算法；图像检索。ABSTRACT：With the continuous development of internet technology, there are a massive amount of image data on the internet, and how to efficiently and quickly find target images from these data has become a common concern. This paper focuses on the research of WEB image sorting and mutual extract algorithm, aiming to facilitate users' fast access and browsing of target images by efficiently sorting and summarizing images.This paper first introduces the current mainstream image retrieval algorithms and WEB image retrieval systems, analyzes their advantages, disadvantages, and existing problems, and proposes the research significance and application value of image sorting and mutual extract algorithms. Secondly, targeted at the two problems of image sorting and mutual extract, this paper proposes specific solutions. Among them, the image sorting algorithm introduces multiple weight factors and uses genetic...
