Fire Detection on Video Using ViBe Algorithm and LBP-TOP

  • Kurniawan Nur Ramadhani Telkom University
  • Febryanti Sthevanie Telkom University
  • Gamma Kosala Telkom University
  • Ketut Sudyatmika Putra Telkom University
Keywords: fire detection, ViBe algorithm, local binary pattern-three orthogonal plane, support vector machine

Abstract

In this research, we built a system to detect fire using the ViBe (Visual Background Extractor) algorithm to extract dynamic targets.  The ViBe algorithm is better at detecting moving target objects such as flame combustion. In this research we combined the ViBe algorithm with three frame differencing to gain better results on movement object. The HSI color space model was applied after the movement object was obtained. We used Local Binary Pattern-Three Orthogonal Planes to obtain the feature extraction to be classified with Support Vector Machine. Our result has shown that the proposed system were able to detect the fire using the LBP-TOP and ViBe algorithm methods with an average accuracy rate of 88.10%, and the best accuracy was 90.37%. The parameters used to achieve this accuracy in the feature extraction process were T=120, Radius=2, and frame gap=15, then the threshold value parameter for three-frame difference parameter was 25.

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References

P. Barmpoutis, P. Papaioannou, K. Dimitropoulos, dan N. Grammalidis, “A Review on Early Forest Fire Detection Systems Using Optical Remote Sensing,” Sensors, vol. 20, no. 22, hlm. 6442, Nov 2020, doi: 10.3390/s20226442.

M. Hashemzadeh dan A. Zademehdi, “Fire detection for video surveillance applications using ICA K-medoids-based color model and efficient spatio-temporal visual features,” Expert Syst. Appl., vol. 130, hlm. 60–78, Sep 2019, doi: 10.1016/j.eswa.2019.04.019.

A. Gaur, A. Singh, A. Kumar, A. Kumar, dan K. Kapoor, “Video Flame and Smoke Based Fire Detection Algorithms: A Literature Review,” Fire Technol., vol. 56, no. 5, hlm. 1943–1980, Sep 2020, doi: 10.1007/s10694-020-00986-y.

M. Torabian, H. Pourghassem, dan H. Mahdavi-Nasab, “Fire Detection Based on Fractal Analysis and Spatio-Temporal Features,” Fire Technol., vol. 57, no. 5, hlm. 2583–2614, Sep 2021, doi: 10.1007/s10694-021-01129-7.

H. Wu, D. Wu, dan J. Zhao, “An intelligent fire detection approach through cameras based on computer vision methods,” Process Saf. Environ. Prot., vol. 127, hlm. 245–256, Jul 2019, doi: 10.1016/j.psep.2019.05.016.

N. Alamgir, K. Nguyen, V. Chandran, dan W. Boles, “Combining multi-channel color space with local binary co-occurrence feature descriptors for accurate smoke detection from surveillance videos,” Fire Saf. J., vol. 102, hlm. 1–10, Des 2018, doi: 10.1016/j.firesaf.2018.09.003.

S. Ali, Md. H. Rahman, dan N. Bouguila, “Fire Detection in Images with Discrete Hidden Markov Models,” dalam Hidden Markov Models and Applications, N. Bouguila, W. Fan, dan M. Amayri, Ed. Cham: Springer International Publishing, 2022, hlm. 81–101. doi: 10.1007/978-3-030-99142-5_4.

Y. Gao dan P. Cheng, “Full-Scale Video-Based Detection of Smoke from Forest Fires Combining ViBe and MSER Algorithms,” Fire Technol., vol. 57, no. 4, hlm. 1637–1666, Jul 2021, doi: 10.1007/s10694-020-01052-3.

D. Niharika dan J. Mohana, “Rule Based Method to Detect Fire and Compare the Accuracy and Precision with Vibe Method,” dalam 2022 International Conference on Business Analytics for Technology and Security (ICBATS), Feb 2022, hlm. 1–5. doi: 10.1109/ICBATS54253.2022.9759061.

M. Jamali, N. Karimi, dan S. Samavi, “Saliency Based Fire Detection Using Texture and Color Features,” dalam 2020 28th Iranian Conference on Electrical Engineering (ICEE), Agu 2020, hlm. 1–5. doi: 10.1109/ICEE50131.2020.9260659.

Y. Bazi dan F. Melgani, “Convolutional SVM Networks for Object Detection in UAV Imagery,” IEEE Trans. Geosci. Remote Sens., vol. 56, no. 6, hlm. 3107–3118, Jun 2018, doi: 10.1109/TGRS.2018.2790926.

J. Olivares-Mercado dkk., “Early Fire Detection on Video Using LBP and Spread Ascending of Smoke,” Sustainability, vol. 11, no. 12, hlm. 3261, Jun 2019, doi: 10.3390/su11123261.

T. Oinosho, M. Kameyama, dan A. Taguchi, “Color Conversion Formulae between RGB Color Space and HSI Color Space for Color Image Processing,” dalam 2021 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS), Nov 2021, hlm. 1–2. doi: 10.1109/ISPACS51563.2021.9651118.

M. Saddique, K. Asghar, U. I. Bajwa, M. Hussain, dan Z. Habib, “Spatial Video Forgery Detection and Localization using Texture Analysis of Consecutive Frames,” Adv. Electr. Comput. Eng., vol. 19, no. 3, hlm. 97–108, 2019, doi: 10.4316/AECE.2019.03012.

V. K. Chauhan, K. Dahiya, dan A. Sharma, “Problem formulations and solvers in linear SVM: a review,” Artif. Intell. Rev., vol. 52, no. 2, hlm. 803–855, Agu 2019, doi: 10.1007/s10462-018-9614-6.

Published
2022-12-27
How to Cite
Kurniawan Nur Ramadhani, Febryanti Sthevanie, Gamma Kosala, & Ketut Sudyatmika Putra. (2022). Fire Detection on Video Using ViBe Algorithm and LBP-TOP. Jurnal RESTI (Rekayasa Sistem Dan Teknologi Informasi), 6(6), 898 - 904. https://doi.org/10.29207/resti.v6i6.4164
Section
Artikel Teknologi Informasi