Optimised Image Storage and Retrieval on Hadoop

Praveen M. Dhulavvagol, Akhilesh Gadagkar, K.J. Ateeth, Gururaj Hegade, Ritik Poonia, S. G. Totad
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Abstract

With the exponential growth of data, it is difficult to efficiently store and retrieve data using traditional methods. There is a need to optimize the storage and to efficiently retrieve relevant data matching the user query. Traditional methods lack optimized storage and to effectively retrieve data. To overcome these limitations, in this project, we propose a distributed architecture framework to optimize memory usage and to effectively retrieve relevant data using Content-Based Image Retrieval (CBIR). The experimental results show that the proposed model enhances storage performance and retrieval time by 20%.
基于Hadoop的优化图像存储和检索
随着数据的指数级增长,使用传统的方法很难有效地存储和检索数据。需要优化存储并有效地检索与用户查询匹配的相关数据。传统方法缺乏优化存储和有效检索数据的能力。为了克服这些限制,在本项目中,我们提出了一个分布式架构框架来优化内存使用,并使用基于内容的图像检索(CBIR)有效地检索相关数据。实验结果表明,该模型的存储性能和检索时间提高了20%。
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