Content Based Image Retrieval for Big Visual Data using Map Reduce

Kumar, Neeraj (2015) Content Based Image Retrieval for Big Visual Data using Map Reduce. Masters thesis, Indian Institute of Technology Hyderabad.

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Abstract

With high availability of portable and low cost digital cameras and improvement in image capture technology, huge amount of visual data (photos and videos) is being generated everyday. The processing capability of standalone devices is insufficient to handle such massive data also known as big data. Apache Hadoop, a distributed computing model that is based on Map Reduce framework is an easy to use solution for managing big data with freely available implementation models. Hadoop is mainly designed for cost-effective commodity hardware or inexpensive cloud computing infrastructure. Hence, access to expensive hardware or in-depth understanding of parallel programming is no longer required to work on big data. With high availability of portable and low cost digital cameras and improvement in image capture technology, huge amount of visual data (photos and videos) is being generated everyday. The processing capability of standalone devices is insufficient to handle such massive data also known as big data. Apache Hadoop, a distributed computing model that is based on Map Reduce framework is an easy to use solution for managing big data with freely available implementation models. Hadoop is mainly designed for cost-effective commodity hardware or inexpensive cloud computing infrastructure. Hence, access to expensive hardware or in-depth understanding of parallel programming is no longer required to work on big data.

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IITH Creators:

IITH Creators	ORCiD

Item Type:

Thesis (Masters)

Uncontrolled Keywords:

Content based image retrieval, clustering, k-means, top-k, data sets, Map Reduce framework, distributed computing model, Apache hadoop , cyclic redundancy check, TD318

Subjects:

Computer science > Computer programming, programs, data
Computer science > Special computer methods

Divisions:

Department of Computer Science & Engineering

Depositing User:

Library Staff

Date Deposited:

29 Jun 2015 10:38

Last Modified:

13 May 2019 11:32

URI:

http://raiithold.iith.ac.in/id/eprint/1609