An Efficient Algorithm Proposed For Smoke Detection in Video Using Hybrid Feature Selection Techniques

Authors

  • P. Matlani Department of Computer Science & Engineering, Guru Ghasidas University, India
  • M. Shrivastava Department of Computer Science & Engineering, Guru Ghasidas University, India
Volume: 9 | Issue: 2 | Pages: 3939-3944 | April 2019 | https://doi.org/10.48084/etasr.2571

Abstract

As an emerging development in the digital technology era, video processing is useful in a wide range of applications. In the current paper, an algorithm is proposed which is useful for smoke detection in video processing. The algorithm quickly detects fire by eliminating common interruptions like noise, overlapping due to the collision, etc. The proposed algorithm is composed of several techniques such as Haar feature, Bhattacharya distance method, SIFT descriptors, Gabor wavelets approach and SVM classifier to identify the smoke by video processing. Foreground object is identified using a moving object algorithm by predicting the movement of smoke in stable images. The implementation has been carried out in MATLAB.

Keywords:

smoke detection, Bhattacharya distance, video processing, bounding box technique, SIFT, Gabor wavelet approach, hybrid algorithm, hill climbing algorithm, moving object algorithm

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References

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How to Cite

[1]
P. Matlani and M. Shrivastava, “An Efficient Algorithm Proposed For Smoke Detection in Video Using Hybrid Feature Selection Techniques”, Eng. Technol. Appl. Sci. Res., vol. 9, no. 2, pp. 3939–3944, Apr. 2019.

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