Framework Implementation of Image-Based Indoor Localization System Using Parallel Distributed Computing 


Vol. 41,  No. 11, pp. 1490-1501, Nov.  2016


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  Abstract

In this paper, we propose an image-based indoor localization system using parallel distributed computing. In order to reduce computation time for indoor localization, an scale invariant feature transform (SIFT) algorithm is performed in parallel by using Apache Spark. Toward this goal, we propose a novel image processing interface of Apache Spark. The experimental results show that the speed of the proposed system is about 3.6 times better than that of the conventional system.

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  Cite this article

[IEEE Style]

B. Kwon, D. Jeon, J. Kim, J. Kim, D. Kim, H. Song, S. Lee, "Framework Implementation of Image-Based Indoor Localization System Using Parallel Distributed Computing," The Journal of Korean Institute of Communications and Information Sciences, vol. 41, no. 11, pp. 1490-1501, 2016. DOI: .

[ACM Style]

Beom Kwon, Donghyun Jeon, Jongyoo Kim, Junghwan Kim, Doyoung Kim, Hyewon Song, and Sanghoon Lee. 2016. Framework Implementation of Image-Based Indoor Localization System Using Parallel Distributed Computing. The Journal of Korean Institute of Communications and Information Sciences, 41, 11, (2016), 1490-1501. DOI: .

[KICS Style]

Beom Kwon, Donghyun Jeon, Jongyoo Kim, Junghwan Kim, Doyoung Kim, Hyewon Song, Sanghoon Lee, "Framework Implementation of Image-Based Indoor Localization System Using Parallel Distributed Computing," The Journal of Korean Institute of Communications and Information Sciences, vol. 41, no. 11, pp. 1490-1501, 11. 2016.

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pISSN : 1226 - 4717
eISSN : 2287 - 3880