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http://dx.doi.org/10.9708/jksci.2015.20.1.001

Implementation and Performance Evaluation of a Video-Equipped Real-Time Fire Detection Method at Different Resolutions using a GPU  

Shon, Dong-Koo (School of Electrical, Electronics, and Computer Engineering, University of Ulsan)
Kim, Cheol-Hong (School of Electronics and Computer Engineering, Chonnam National University)
Kim, Jong-Myon (School of Electrical, Electronics, and Computer Engineering, University of Ulsan)
Publication Information
Journal of the Korea Society of Computer and Information / v.20, no.1, 2015 , pp. 1-10 More about this Journal
Abstract
In this paper, we propose an efficient parallel implementation method of a widely used complex four-stage fire detection algorithm using a graphics processing unit (GPU) to improve the performance of the algorithm and analyze the performance of the parallel implementation method. In addition, we use seven different resolution videos (QVGA, VGA, SVGA, XGA, SXGA+, UXGA, QXGA) as inputs of the four-stage fire detection algorithm. Moreover, we compare the performance of the GPU-based approach with that of the CPU implementation for each different resolution video. Experimental results using five different fire videos with seven different resolutions indicate that the execution time of the proposed GPU implementation outperforms that of the CPU implementation in terms of execution time and takes a 25.11ms per frame for the UXGA resolution video, satisfying real-time processing (30 frames per second, 30fps) of the fire detection algorithm.
Keywords
Fire detection method; graphics processing unit; real-time processing; video resolution;
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Times Cited By KSCI : 3  (Citation Analysis)
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