Hadoop and Its Role in Modern Image Processing


This paper introduces MapReduce as a distributed data processing model using open source Hadoop framework for manipulating large volume of data. The huge volume of data in the modern world, particularly multimedia data, creates new requirements for processing and storage. As an open source distributed computational framework, Hadoop allows for processing large amounts of images on an infinite set of computing nodes by providing necessary infrastructures. This paper introduces this framework, current works and its advantages and disadvantages.

Share and Cite:

Banaei, S. and Moghaddam, H. (2014) Hadoop and Its Role in Modern Image Processing. Open Journal of Marine Science, 4, 239-245. doi: 10.4236/ojms.2014.44022.

Conflicts of Interest

The authors declare no conflicts of interest.


[1] Gartner Reserch (2012) Top 10 Strategic Technologies for 2012.
[2] Bakshi, K. (2012) Considerations for Big Data: Architecture and Approach. Aerospace Conference-Big Sky, MT, 3-10 March 2012.
[3] Michael, K. and Miller, K.W. (2013) Big Data: New Opportunities and New Challenges. Journal of IEEE Computer Society, 46, 22-24.
[4] White, B., Tom, Y., Jimmy, L. and Davis, L.S. (2010) Web-Scale Computer Vision Using MapReduce for Multimedia Data Mining. Proceedings of the 10th International Workshop on Multimedia Data Mining, Washington DC, 25-28 July 2010, 1-10.
[5] Dean, J. and Ghemawat, S. (2008) MapReduce: Simplified Data Processing on Large Clusters. Communications of the ACM, 51, 107-114.
[6] The New York Times Blog (2007)
[7] Kalagiakos, P. (2011) Cloud Computing Learning. Application of Information and Communication Technologies (AICT). 5th International Conference, 12-14 October 2011.
[8] Hadoop. http://hadoop.apache.org/
[9] http://en.wikipedia.org/wiki/Apache_Hadoop
[10] HDFS. http://hadoop.apache.org/hdfs/
[11] MapReduce. http://en.wikipedia.org/wiki/MapReduce
[12] Bhandarkar, M. (2010) MapReduce Programming with Apache Hadoop. Parallel &Distributed Processing (IPDPS) IEEE, 19-23 April 2010.
[13] Kelly, J. (2012) Big Data: Hadoop, Business Analytics and Beyond. Wikibon Whitepaper, 27 August 2012.
[14] http://hadooper.blogspot.com/
[15] Twister. http://www.iterativemapreduce.org/
[16] The Phoenix System for MapReduce Programming.
[17] Qura Question and Answer Website.
[18] Li, Y., Crandall, D.J. and Huttenlocher, D.P. (2009) Landmark Classification in Large-Scale Image Collections. ICCV, 1957-1964.
[19] Kennedy, L., Slaney, M. and Weinberger, K. (2009) Reliable Tags Using Image Similarity: Mining Specificity and Expertise from Large-Scale Multimedia Databases. Proceedings of the 1st Workshop on Web-Scale Multimedia Corpus, Beijing, 23-23 October 2009, 17-24.
[20] Yan, R., Fleury, M.-O., Merler, M., Natsev, A. and Smith, J.R. (2009) Large-Scale Multimedia Semantic Concept Modeling Using Robust Subspace Bagging and MapReduce. Proceedings of the 1st ACM Workshop on Large-Scale Multimedia Retrieval and Mining, Beijing, 23-23 October 2009, 35-42.
[21] Shi, L.L., Wu, B., Wang, B. and Yan, X.G. (2011) Map/Reduce in CBIR Application. 2011 International Conference on Computer Science and Network Technology (ICCSNT), Vol. 4, Harbin, 24-26 December 2011, 2465-2468.
[22] Zhao, J.Y., Li, Q. and Zhou, H.W. (2011) A Cloud-Based System for Spatial Analysis Service. 2011 International Conference on Remote Sensing, Environment and Transportation Engineering (RSETE), Nanjing, 24-26 June 2011, 1-4.
[23] Yang, C.-T. and Chen, L.-T., Chou, W.-L. and Wang, K.-C. (2010) Implementation of a Medical Image File Accessing System on Cloud Computing. 2010 IEEE 13th International Conference on Computational Science and Engineering (CSE), Hong Kong, 11-13 December 2010, 321-326.
[24] Shelly and Raghava, N.S. (2011) Iris Recognition on Hadoop: A Biometrics System Implementation on Cloud Computing. 2011 IEEE International Conference on Cloud Computing and Intelligence Systems (CCIS), Beijing, 15-17 September 2011, 482-485.
[25] Kocakulak, H. and Temizel, T.T. (2011) A Hadoop Solution for Ballistic Image Analysis and Recognition. 2011 International Conference on High Performance Computing and Simulation (HPCS), Istanbul, 4-8 July 2011, 836-842.
[26] Almeer, M.H. (2012) Cloud Hadoop MapReduce For Remote Sensing Image Analysis. Journal of Emerging Trends in Computing and Information Sciences, 3, 637-644.
[27] Bajcsy, P., Vandecreme, A., Amelot, J., Nguyen, P., Chalfoun, J. and Brady, M. (2013) Terabyte-Sized Image Computations on Hadoop Cluster Platforms. 2013 IEEE International Conference on Big Data, Silicon Valley, 6-9 October 2013, 729-737.
[28] Storm Project. http://storm.incubator.apache.org/
[29] Samza Project. http://samza.incubator.apache.org/

Copyright © 2023 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.