A General Framework for Big Image Data using Hierarchical Distribution
- MapReduce, distributed system, cloud processing, big image data, image processing, and parallel processing.
This introduce the ICP framework it provide the general framework for image processing field to achieve efficient result, time efficiency and high quality result and also increase the image scale these all are implemented in parallel. Here we have two mechanisms Static image cloud processing (SICP) and Dynamic image cloud processing(DICP). SICP is used processing the large scale image data pre stored in distributed system; DICP is used for dynamic input. SICP has two types of image data P-image and Big-image are designed using MapReduce to achieve optimized configuration and higher efficiency. DICP implemented using the parallel processing procedure with old-style processing mechanism of the distributed system.
"A General Framework for Big Image Data using Hierarchical Distribution", IJSDR - International Journal of Scientific Development and Research (www.IJSDR.org), ISSN:2455-2631, Vol.3, Issue 5, page no.112 - 117, May-2018, Available :https://ijsdr.org/papers/IJSDR1805019.pdf
Volume 3
Issue 5,
May-2018
Pages : 112 - 117
Paper Reg. ID: IJSDR_180071
Published Paper Id: IJSDR1805019
Downloads: 000347230
Research Area: Engineering
Country: Tumkur, Karnataka, India
ISSN: 2455-2631 | IMPACT FACTOR: 9.15 Calculated By Google Scholar | ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 9.15 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publisher: IJSDR(IJ Publication) Janvi Wave
