• KSII Transactions on Internet and Information Systems
    Monthly Online Journal (eISSN: 1976-7277)

A Video Smoke Detection Algorithm Based on Cascade Classification and Deep Learning


Abstract

Fires are a common cause of catastrophic personal injuries and devastating property damage. Every year, many fires occur and threaten human lives and property around the world. Providing early important sign for early fire detection, and therefore the detection of smoke is always the first step in fire-alarm systems. In this paper we propose an automatic smoke detection system built on camera surveillance and image processing technologies. The key features used in our algorithm are to detect and track smoke as moving objects and distinguish smoke from non-smoke objects using a convolutional neural network (CNN) model for cascade classification. The results of our experiment, in comparison with those of some earlier studies, show that the proposed algorithm is very effective not only in detecting smoke, but also in reducing false positives.


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Cite this article

[IEEE Style]
Nguyen Manh Dung, Dongkeun Kim and Soonghwan Ro, "A Video Smoke Detection Algorithm Based on Cascade Classification and Deep Learning," KSII Transactions on Internet and Information Systems, vol. 12, no. 12, pp. 6018-6033, 2018. DOI: 10.3837/tiis.2018.12.022

[ACM Style]
Dung, N. M., Kim, D., and Ro, S. 2018. A Video Smoke Detection Algorithm Based on Cascade Classification and Deep Learning. KSII Transactions on Internet and Information Systems, 12, 12, (2018), 6018-6033. DOI: 10.3837/tiis.2018.12.022