Smoke detection for static cameras

Abstract

This paper describes the smoke detection for static cameras. The background subtraction was used to determine moving objects. Color characteristics were utilized to distinguish smoke regions and other scene members. Separate pixels were united into blobs by morphology operations and connected components labeling methods. The image is then refined by boundary roughness and edge density to decrease amount of false detections. Results of the current frame are compared to the previous one in order to check the behavior of objects in time domain.

DOI: 10.1109/FCV.2015.7103719

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Cite this paper

@article{Filonenko2015SmokeDF, title={Smoke detection for static cameras}, author={Alexander Filonenko and Danilo C{\'a}ceres Hern{\'a}ndez and Kang-Hyun Jo}, journal={2015 21st Korea-Japan Joint Workshop on Frontiers of Computer Vision (FCV)}, year={2015}, pages={1-4} }