Research Article Open Access

Processing Large Volume of Biometric Data in the Hadoop Single Cluster Node Environment

Jayakumar Vaithiyashankar1, Shohel Sayeed1 and Anang Muhammad Amin1
  • 1 Faculty of Information Science and Technology, Multimedia University, Malaysia

Abstract

In big data evolution, the analysis of large scale data and scrutinizing the required vital information becomes very demanding task. The emerging cloud platform promises and gives hope in handling the enormous volume of data. Hence, a new kind of methodology is required to tap the full potential of leveraging the big data analytics over the biometric data. In this work, we are going to deal with the integration of Hadoop, a map reduce framework with the infamous powerful computer vision library tool, Opencv. The proposed setup will comparatively analyze the large set of biometric data; such as face over the pseudo distributed environment. We test the capacity of our methodology with a different data set and analyze various computational parameters. The results show the proposed method is applicable for dealing in the real distributed environment. 

American Journal of Applied Sciences
Volume 14 No. 12, 2017, 1075-1080

DOI: https://doi.org/10.3844/ajassp.2017.1075.1080

Submitted On: 28 February 2017 Published On: 27 October 2017

How to Cite: Vaithiyashankar, J., Sayeed, S. & Amin, A. M. (2017). Processing Large Volume of Biometric Data in the Hadoop Single Cluster Node Environment. American Journal of Applied Sciences, 14(12), 1075-1080. https://doi.org/10.3844/ajassp.2017.1075.1080

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Keywords

  • Biometrics
  • Cloud Computing
  • Distributed Computing
  • Personal Identification
  • Face Recognition
  • Computer Vision