CFP last date
02 December 2024
Call for Paper
January Edition
CAE solicits high quality original research papers for the upcoming January edition of the journal. The last date of research paper submission is 02 December 2024

Submit your paper
Know more
The week's pick
Responsive image
Property (Land) Registration Management Using Blockchain in Nigeria

A. Festus Osuolale Ojebiyi David-Daniel Seriki Oluwasogo
Random Articles
Reseach Article

Effective and Faster Retrieval of Images from Large Database by using Binary Tree Implemented with Map Reduce

by Radhakrishnan B., Anver Muhammed K.M.
journal cover thumbnail

Communications on Applied Electronics
Foundation of Computer Science (FCS), NY, USA
Volume 4 - Number 7
Year of Publication: 2016
Authors: Radhakrishnan B., Anver Muhammed K.M.
10.5120/cae2016652126

Radhakrishnan B., Anver Muhammed K.M. . Effective and Faster Retrieval of Images from Large Database by using Binary Tree Implemented with Map Reduce. Communications on Applied Electronics. 4, 7 ( March 2016), 7-10. DOI=10.5120/cae2016652126

@article{ 10.5120/cae2016652126,
author = { Radhakrishnan B., Anver Muhammed K.M. },
title = { Effective and Faster Retrieval of Images from Large Database by using Binary Tree Implemented with Map Reduce },
journal = { Communications on Applied Electronics },
issue_date = { March 2016 },
volume = { 4 },
number = { 7 },
month = { March },
year = { 2016 },
issn = { 2394-4714 },
pages = { 7-10 },
numpages = {9},
url = { https://www.caeaccess.org/archives/volume4/number7/563-2016652126/ },
doi = { 10.5120/cae2016652126 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2023-09-04T19:53:43.950228+05:30
%A Radhakrishnan B.
%A Anver Muhammed K.M.
%T Effective and Faster Retrieval of Images from Large Database by using Binary Tree Implemented with Map Reduce
%J Communications on Applied Electronics
%@ 2394-4714
%V 4
%N 7
%P 7-10
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Effective searching of image from large image data base is definitely a tedious task. Searching images linearly will cost a lot of time. A distributed approach using map reduce concept is proposed in this paper. Rather than comparing two images, similarity features between images are searched for. The features are stored in different machines which are implemented using two dimensional binary tree. The tree constitutes the root and leaf machine which des the necessitated search.

References
  1. Ilaria Bartolini, Paolo Ciaccia, an d Marco Patella. A sound algorithm for region-based image retrieval using an index. In proceedings of the 4th International Workshop on Query Processing and Multimedia Issue in Distributed Systems (QPMIDS’00), pages 930–934, Greenwich, London, UK, September 2000.
  2. Ilaria Bartolini, Paolo Ciaccia, and Florian Waas. Feedback Bypass: A new approach to interactive similarity query processing. Technical Report CSITE-09-01, CSITE–CNR, 2001. Available at URL http://www-db.deis.unibo.it/ MMDBGroup/TRs.html.
  3. Stefan Berchtold, Daniel A. Keim, and Hans-Peter Kriegel. The X-tree: An index structure for high-dimensional data. In Proceedings of the 22nd International conference on Very Large Data Bases (VLDB’96), pages 28–39, Mumbai (Bombay), India, September 1996.
  4. Christos Faloutsos, Will Equitz, Myron Flickner, Wayne Niblack, Dragutin Petkovic, and Ron Barber. Efficient and effective querying by image content. Journal of Intelligent Information Systems, 3(3/4):231–262, July 1994.
  5. Yong Rui, Thomas S. Huang, Michael Ortega, and Sharad Mehrotra. Relevance feedback: A power tool for interactive content-based image retrieval. IEEE transaction on Circuits and Systems for Video Technology, 8(5):644–655, September 1998.
  6. Mohamed Aly, Mario Munich, and Pietro Perona. Indexing in large scale image collections: Scaling properties and benchmark. In WACV, 2011.
  7. Ulrich Buddemeier and Alessandro Bissaccoo. Distributed kd-tree for efficient approximate nearest neighbor search, 2009.
  8. M. Muja and D. Lowe. Fast approximate nearest neighbors with automatic algorithm configuration. In VISAPP, 2009.
  9. J. Zobel and A. Moffat. Inverted files for text search engines. ACM Comput. Surv., 2006. ISSN 0360-0300.
  10. T.Cormen,C.Leiserson, R. Rivest, and C. Stein. Introduction to Algorithms. McGraw- Hill, 2001.
  11. Jeffrey Dean and Sanjay Ghemawat. Mapreduce: Simplified data processing on large clusters. In OSDI, 2004.
  12. H. Jégou, M. Douze, C. Schmid, and P. Pérez. Aggregating local descriptors into a compact image representation. In CVPR, 2010.
  13. S. Arya, D.M. Mount, N.S. Netanyahu, R. Silverman, and A.Y. Wu. An optimal algorithm for approximate nearest neighbor searching. Journal of the ACM, 45:891– 923, 1998.
Index Terms

Computer Science
Information Sciences

Keywords

CBIR Map Reduce Feature vectors.

Powered by PhDFocusTM