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.

[img] Text
CS12M1006.pdf - Submitted Version
Restricted to Registered users only until 30 June 2018.

Download (2MB) | Request a copy

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.

[error in script]
IITH Creators:
IITH CreatorsORCiD
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: 10 Jul 2015 06:01
URI: http://raiith.iith.ac.in/id/eprint/1609
Publisher URL:
Related URLs:

Actions (login required)

View Item View Item
Statistics for RAIITH ePrint 1609 Statistics for this ePrint Item