P.S. Vijayalakshmi1
, K. Gomathy2
, C. Kumuthini3
Section:Review Paper, Product Type: Journal Paper
Volume-06 ,
Issue-08 , Page no. 9-14, Oct-2018
CrossRef-DOI:
https://doi.org/10.26438/ijcse/v6si8.914
Online published on Oct 31, 2018
Copyright © P.S. Vijayalakshmi, K. Gomathy, C. Kumuthini . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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IEEE Style Citation: P.S. Vijayalakshmi, K. Gomathy, C. Kumuthini, “HIPI: A REVIEW ON HADOOP MAP REDUCE FRAMEWORK USING IMAGE PROCESSING IN BIGDATA,” International Journal of Computer Sciences and Engineering, Vol.06, Issue.08, pp.9-14, 2018.
MLA Style Citation: P.S. Vijayalakshmi, K. Gomathy, C. Kumuthini "HIPI: A REVIEW ON HADOOP MAP REDUCE FRAMEWORK USING IMAGE PROCESSING IN BIGDATA." International Journal of Computer Sciences and Engineering 06.08 (2018): 9-14.
APA Style Citation: P.S. Vijayalakshmi, K. Gomathy, C. Kumuthini, (2018). HIPI: A REVIEW ON HADOOP MAP REDUCE FRAMEWORK USING IMAGE PROCESSING IN BIGDATA. International Journal of Computer Sciences and Engineering, 06(08), 9-14.
BibTex Style Citation:
@article{Vijayalakshmi_2018,
author = {P.S. Vijayalakshmi, K. Gomathy, C. Kumuthini},
title = {HIPI: A REVIEW ON HADOOP MAP REDUCE FRAMEWORK USING IMAGE PROCESSING IN BIGDATA},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {10 2018},
volume = {06},
Issue = {08},
month = {10},
year = {2018},
issn = {2347-2693},
pages = {9-14},
url = {https://www.ijcseonline.org/full_spl_paper_view.php?paper_id=466},
doi = {https://doi.org/10.26438/ijcse/v6i8.914}
publisher = {IJCSE, Indore, INDIA},
}
RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v6i8.914}
UR - https://www.ijcseonline.org/full_spl_paper_view.php?paper_id=466
TI - HIPI: A REVIEW ON HADOOP MAP REDUCE FRAMEWORK USING IMAGE PROCESSING IN BIGDATA
T2 - International Journal of Computer Sciences and Engineering
AU - P.S. Vijayalakshmi, K. Gomathy, C. Kumuthini
PY - 2018
DA - 2018/10/31
PB - IJCSE, Indore, INDIA
SP - 9-14
IS - 08
VL - 06
SN - 2347-2693
ER -
Nowadays, Big data is growing vey faster in the world. Big data is the large volume of data that consists of both structured and unstructured on a day-to-day basis. But it`s not the amount of data. Big data is the data which includes sensor data, biometric data, Geo-spatial, Healthcare, power grid, transport, search engine and in Social networks. Hadoop process large amounts of data, in parallel, clusters of commodity hardware in a reliable and fault-tolerant manner. In this paper we review the Image processing using Map reduce technique with the help of HIPI (the image processing Tool).
Hadoop, Map reduce, Big data, Image Processing, HIPI
[1] https://zephoria.com/top-15-valuable-facebook-statistics
[2]Hadoop map reduce framework.http://hadoop.apache.org/mapreduce/.
[3]Customizing input file formats for image processing in hadoop. Arizona State University. Online at:
http://hpc. asu. edu/node/97.
[4]DEAN, J.,AND GHEMAWAT,S.2008. Mapreduce: Simplified data processing on large clusters. Communications of the ACM 51, 1,107–113.
[5] PDF: HIPI: A Hadoop Image Processing Interface for Image-based Map Reduce Tasks. Available from: https://www.researchgate.net/publication/266464321_HIPI_A_Hadoop_Image_Processing_Interface_for_Image-based_MapReduce_Tasks [accessed Jul 18 2018].
[6] http://hipi.cs.virginia.edu/
[7] https://github.com/uvagfx/hipi
[8] http://hipi.cs.virginia.edu/gettingstarted.html
[9] http://hipi.cs.virginia.edu/examples.html
