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Second order-based image retrieval algorithm

机译:基于二阶的图像检索算法

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摘要

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.
机译:在大数据环境下,检索成为一项关键技术,图像检索受到越来越多的关注和广泛的应用。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,提取图像筛选特征。然后,通过k均值聚类和词袋算法建立特征词频表。最后,基于词频表,首先检索具有相似结构分布特征的图像。二阶检索根据属于同一类别的对应特征点的比例实现图像的精确检索。实验结果表明,该方法具有良好的查全率,对查询效率有良好的效果。这是一种可以使用的方法。

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