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An efficient indexing method for content-based image retrieval

机译:一种基于内容的图像检索的高效索引方法

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摘要

In this paper, we propose an efficient indexing method for content-based image retrieval. The proposed method introduces the ordered quantization to increase the distinction among the quantized feature descriptors. Thus, the feature point correspondences can be determined by the quantized feature descriptors, and they are used to measure the similarity between query image and database image. To implement the above scheme efficiently, a multi-dimensional inverted index is proposed to compute the number of feature point correspondences, and then approximate RANSAC is investigated to estimate the spatial correspondences of feature points between query image and candidate images returned from the multi-dimensional inverted index. The experimental results demonstrate that our indexing method improves the retrieval efficiency while ensuring the retrieval accuracy in the content-based image retrieval.
机译:在本文中,我们提出了一种有效的基于内容的图像检索索引方法。所提出的方法引入有序量化以增加量化特征描述符之间的区别。因此,可以通过量化的特征描述符来确定特征点对应关系,并将它们用于测量查询图像与数据库图像之间的相似度。为了有效地实现上述方案,提出了一种多维倒排索引来计算特征点对应的数量,然后研究近似RANSAC来估计查询图像与多维返回的候选图像之间特征点的空间对应。倒排索引。实验结果表明,我们的索引方法在确保基于内容的图像检索中的检索精度的同时,提高了检索效率。

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