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http://dx.doi.org/10.9708/jksci.2013.18.9.001

Parallel Implementation and Performance Evaluation of the SIFT Algorithm Using a Many-Core Processor  

Kim, Jae-Young (School of Electrical Engineering, University of Ulsan)
Son, Dong-Koo (School of Electrical Engineering, University of Ulsan)
Kim, Jong-Myon (School of Electrical Engineering, University of Ulsan)
Jun, Heesung (School of Electrical Engineering, University of Ulsan)
Abstract
In this paper, we implement the SIFT(Scale-Invariant Feature Transform) algorithm for feature point extraction using a many-core processor, and analyze the performance, area efficiency, and system area efficiency of the many-core processor. In addition, we demonstrate the potential of the proposed many-core processor by comparing the performance of the many-core processor with that of high-performance CPU and GPU(Graphics Processing Unit). Experimental results indicate that the accuracy result of the SIFT algorithm using the many-core processor was same as that of OpenCV. In addition, the many-core processor outperforms CPU and GPU in terms of execution time. Moreover, this paper proposed an optimal model of the SIFT algorithm on the many-core processor by analyzing energy efficiency and area efficiency for different octave sizes.
Keywords
Many-core processor; SIFT; parallel processing; graphics processing unit; energy efficiency; system area efficiency;
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Times Cited By KSCI : 2  (Citation Analysis)
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