Processing Large Volume of Biometric Data in the Hadoop Single Cluster Node Environment
- 1 Faculty of Information Science and Technology, Multimedia University, Malaysia
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.
Copyright: © 2017 Jayakumar Vaithiyashankar, Shohel Sayeed and Anang Muhammad Amin. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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- Cloud Computing
- Distributed Computing
- Personal Identification
- Face Recognition
- Computer Vision