Early fire detection algorithm based on irregular patterns of flames and hierarchical Bayesian Networks

Ko, Byoung Chul; Cheong, Kwang-Ho; Nam, Jae-Yeal

doi:10.1016/j.firesaf.2010.04.001

Cited by 100 publications

(38 citation statements)

References 10 publications

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“…Flames with high lightness, reddish color, a distinct movement frequency distribution and other features appear distinct in video and many related flame detection algorithms have been proposed [1][2][3][4][5][6]. According to the law of fire development, a fire will grow exponentially after an open flame develops.…”

Section: Introductionmentioning

confidence: 99%

A Saliency-Based Method for Early Smoke Detection in Video Sequences

et al. 2015

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Video-based smoke detection requires suspected smoke regions to be segmented from the complex background in the initial stage of detection. This segmentation is also important to the subsequent processes of detection. This paper proposes a novel method of segmenting a smoke region in smoke pixel classification based on saliency detection. A salient smoke detection model based on color and motion features is used. First, smoke regions are identified by enhancing the smoke color nonlinearly. The enhanced map and motion map are then used to measure saliency. Finally, the motion energy and saliency map are used to estimate the suspected smoke regions. The estimation result is regarded as our final smoke pixel segmentation result. The performance of the proposed algorithm is verified on a set of videos containing smoke. In the experiments, the method achieves average smoke segmentation precision of 93.0%, and the precision is as high as 99.0% for forest fires. The results are compared with those of three other methods used in the literature, revealing the proposed method to have both a better segmentation result and better precision. We also present encouraging results of smoke segmentation in video sequences obtained using the proposed saliency detection method. Furthermore, the proposed smoke segmentation method can be used for real-time fire detection in color video sequences.

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Section: Introductionmentioning

confidence: 99%

A Saliency-Based Method for Early Smoke Detection in Video Sequences

et al. 2015

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“…Well-known moving object detection algorithms are background (BG) subtraction methods [16,21,18,14,13,17,20,22,27,28,30,34], temporal differencing [19], and optical flow analysis [9,8,29]. They can all be used as part of a VFD system.…”

Section: Moving Object Detectionmentioning

confidence: 99%

“…As it is well-known, flames flicker in uncontrolled fires, therefore flicker detection [24,18,12,13,27,28,30] in video and wavelet-domain signal energy analysis [21,14,20,26,31,39] can be used to distinguish ordinary objects from fire. These methods focus on the temporal behavior of flames and smoke.…”

Section: Motion and Flicker Analysis Using Fourier And Wavelet Transfmentioning

confidence: 99%

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Video fire detection – Review

Çetin

Dimitropoulos

Gouverneur

et al. 2013

Digital Signal Processing

237

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This is a review article describing the recent developments in Video based Fire Detection (VFD). Video surveillance cameras and computer vision methods are widely used in many security applications. It is also possible to use security cameras and special purpose infrared surveillance cameras for fire detection. This requires intelligent video processing techniques for detection and analysis of uncontrolled fire behavior. VFD may help reduce the detection time compared to the currently available sensors in both indoors and outdoors because cameras can monitor "volumes" and do not have transport delay that the traditional "point" sensors suffer from. It is possible to cover an area of 100 km2 using a single pan-tilt-zoom camera placed on a hilltop for wildfire detection. Another benefit of the VFD systems is that they can provide crucial information about the size and growth of the fire, direction of smoke propagation.

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“…In many cases, smoke alarms are combined with other detection technologies (such as gas and heat sensors) to ensure an efficient and reliable detection of the early indicators of fire occurrence [3][4][5][6]. For extra protection against fire, however, in addition to smoke alarms, installation of fire sprinklers is recommended.…”

Section: Introductionmentioning

confidence: 99%

Development of a Smart Residential Fire Protection System

Jiang

Panganiban

2013

Advances in Mechanical Engineering

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Embedded system is applied for the development of smart residential fire detection and extinguishing system. Wireless communication capability is integrated into various fire sensors and alarm devices. The system activates the fire alarm to warn occupants, executes emergency and rescue calls to remote residents and fire-fighting facility in an intelligent way. The effective location of extra-sprinklers within the space of interest for the fire extinguishing system is also investigated. Actual fire test suggests that the developed wireless system for the smart residential fire protection system is reliable in terms of sensors and their communication linkage.

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Early fire detection algorithm based on irregular patterns of flames and hierarchical Bayesian Networks

Cited by 100 publications

References 10 publications

A Saliency-Based Method for Early Smoke Detection in Video Sequences

A Saliency-Based Method for Early Smoke Detection in Video Sequences

Video fire detection – Review

Development of a Smart Residential Fire Protection System

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