一种基于位置敏感散列的大规模基于内容的图像检索方法

Weihong Wang, Song Wang
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引用次数: 3

摘要

基于内容的图像检索(CBIR)技术面临的一个关键挑战是如何开发一种快速的高维图像内容索引方法,这对于构建大规模的图像检索系统至关重要。在本文中,我们提出了一种使用位置敏感哈希(LSH)的可扩展的基于内容的图像检索方案,并在50万张图像的大型图像测试平台上进行了广泛的评估。据我们所知,目前对50万张图像的大规模CBIR评价的研究还不够全面。我们的实证结果表明,我们提出的解决方案能够扩展到数十万张图像,这对于构建web规模的CBIR系统是有希望的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A method using locality-sensitive hashing for large-scale content-based image retrieval
To develop a fast solution for indexing high-dimensional image contents, which is crucial to building large-scale CBIR systems, is one key challenge in content-based image retrieval(CBIR). In this paper, we propose a scalable content-based image retrieval scheme using locality-sensitive hashing (LSH), and conduct extensive evaluations on a large image testbed of a half million images. To the best of our knowledge, there is less comprehensive study on large-scale CBIR evaluation with a half million images. Our empirical results show that our proposed solution is able to scale for hundreds of thousands of images, which is promising for building web-scale CBIR systems.
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