基于禁忌表的图像检索相关反馈新算法

Decai Huang, Jia Hu, Yuan Yuan
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引用次数: 0

摘要

在基于内容的图像检索研究中,以往的工作主要集中在眼部特征的选择和提取上。但是这种检索系统不能满足实际使用的期望,因为它既不能充分利用人的主观性,也不能将图像的底层特征与图像的语义内容相结合。为了解决这一问题,本文采用区域权重自动调整和禁忌搜索算法相结合的方案,提出了一种基于禁忌搜索的图像检索相关反馈算法。实验结果表明,该算法对区域权值进行调整后效果良好。检索性能得到了明显的提高
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Novel Relevance Feedback Algorithm with Tabu-list in Image Retrieval
In the research of content-based image retrieval, the former work was focused on the choice and the extraction of ocular features principally. But this kind of retrieval system cannot meet the expectations of practical use, because it can neither make full use of people's subjectivity, nor integrate low-level image features with semantic contents of images. In order to solve this problem, this paper uses the scheme of region weight adjusted automatically and tabu search algorithm, presents a tabu search-based relevance feedback algorithm in image retrieval. The experimental results show that after the region weight adjusted by this algorithm. The retrieval performance is improved very obviously
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