基于二阶的图像检索算法

Daguang Jiang, Junkai Yi
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引用次数: 0

摘要

在大数据环境下,检索成为一项关键技术,图像检索越来越受到重视和广泛应用。本文提出了一种二阶检索算法,该算法可用于检索相似图像。首先,提取图像sift特征。然后,通过k-均值聚类和词袋算法构建特特词频率表。最后,基于词频表,首先检索出具有相似结构分布特征的图像。二阶检索根据对应的特征点属于同一类的比例实现对图像的精确检索。实验结果表明,该方法具有良好的查全率和查询效率。这是一种可以使用的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Second order-based image retrieval algorithm
Under the environment of big data, retrieval becomes a crucial technology and image retrieval is paid more attention and widely used. The paper proposes a second-order retrieval algorithm, of which can be used to retrieval the similar images. Firstly, extracting image sift features. Then, build frequency table of characteristic words by k-means clustering and bag of word algorithm. Finally, based on word frequency table, first retrieve the images that have similar distribution characteristics of the structure. The second-order retrieval implement accurate retrieval of images according to the proportion of the corresponding feature points that belonging to the same class. The experimental results show that this method has good recall factor and good effect on query efficiency. It's a kind of method can be used.
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