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Content-Based Image Retrial Based on Hadoop

机译:基于Hadoop的基于内容的图像重试

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摘要

Generally, time complexity of algorithms for content-based image retrial is extremely high. In order to retrieve images on large-scale databases efficiently, a new way for retrieving based on Hadoop distributed framework is proposed. Firstly, a database of images features is built by using Speeded Up Robust Features algorithm and Locality-Sensitive Hashing and then perform the search on Hadoop platform in a parallel way specially designed. Considerable experimental results show that it is able to retrieve images based on content on large-scale cluster and image sets effectively.
机译:通常,用于基于内容的图像重试的算法的时间复杂度非常高。为了有效地在大型数据库上检索图像,提出了一种新的基于Hadoop分布式框架的检索方法。首先,使用“加速鲁棒特征算法”和“局部敏感哈希”建立图像特征数据库,然后以专门设计的并行方式在Hadoop平台上执行搜索。大量的实验结果表明,它能够基于大规模聚类和图像集上的内容有效地检索图像。

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