Forest Fire Smoke Detection in Video Based on Digital Image Processing Approach with Static and Dynamic Characteristic Analysis

Surit, Surapong; Chatwiriya, Watchara

doi:10.1109/cnsi.2011.47

Cited by 27 publications

(16 citation statements)

References 4 publications

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“…Although the results are promising, further development is still needed to integrate such findings with existing surveillance systems and implement them in actual operations. An approach using static and dynamic characteristic analysis for forest fire smoke detection is proposed by Surit and Chatwiriya (2011). Zhang et al (2007) present an Otsu-based method to detect fire and smoke while segmenting fire and smoke together from the background.…”

Section: Fire Detection With Visual Imagesmentioning

confidence: 99%

A survey on technologies for automatic forest fire monitoring, detection, and fighting using unmanned aerial vehicles and remote sensing techniques

2015

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Because of their rapid maneuverability, extended operational range, and improved personnel safety, unmanned aerial vehicles (UAVs) with vision-based systems have great potential for monitoring, detecting, and fighting forest fires. Over the last decade, UAV-based forest fire fighting technology has shown increasing promise. This paper presents a systematic overview of current progress in this field. First, a brief review of the development and system architecture of UAV systems for forest fire monitoring, detection, and fighting is provided. Next, technologies related to UAV forest fire monitoring, detection, and fighting are briefly reviewed, including those associated with fire detection, diagnosis, and prognosis, image vibration elimination, and cooperative control of UAVs. The final section outlines existing challenges and potential solutions in the application of UAVs to forest firefighting.Résumé : Étant donné qu'ils sont rapidement manoeuvrables, qu'ils ont un grand rayon d'action opérationnel et qu'ils offrent une meilleure sécurité pour le personnel, les véhicules aériens sans pilote (UAV) équipés de systèmes de vision ont un potentiel énorme pour surveiller, détecter et combattre les feux de forêt. Au cours de la dernière décennie, la technologie de lutte contre les feux de forêt qui utilise des UAV s'est avérée de plus en plus prometteuse. Cet article présente un aperçu complet des progrès actuels dans ce domaine. D'abord, une brève revue du développement et de l'architecture des systèmes de surveillance, de détection et de combat des feux de forêt qui utilisent des UAV est présentée. Ensuite, les technologies reliées à la surveillance, à la détection et au combat des feux de forêt sont brièvement passées en revue, incluant celles qui sont associées à la détection, au diagnostic et au pronostic des feux, à l'élimination de la vibration des images et au contrôle coopératif des UAV. La dernière section décrit les défis actuels et les solutions potentielles liés à l'utilisation des UAV dans la lutte contre les feux de forêt. [Traduit par la Rédaction] Mots-clés : feu de forêt, surveillance, détection et combat des feux, traitement des images, télédétection, véhicules aériens sans pilote.

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Section: Fire Detection With Visual Imagesmentioning

confidence: 99%

A survey on technologies for automatic forest fire monitoring, detection, and fighting using unmanned aerial vehicles and remote sensing techniques

2015

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“…(4) According to the results, the corresponding gray level is selected as the optimal threshold when the variance between classes is taken as the maximum. Note that OTSU uses the value of inter-class variance to represent the difference of image gray level [11]. Taking into account the presence of noise disturbance in the video frames and the moving target in the presence of close to the background color, these factors may make the result of moving target detection is not very well.…”

Section: Flow Chart Of Smoke Detection Algorithmmentioning

confidence: 99%

Networked Video Smoke and Fire Monitoring System Based on DM642 and i.MX27

Hong¹,

Xia²,

Liu³

et al. 2017

IJSH

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In this paper, a networked video smoke and fire detector based on TMS320DM642 and i.MX27 is designed. The design of the system hardware, software platform and detection algorithm will be introduced. In order to improve the accuracy of smoke detection and reduce the false alarm rate, color, energy and structural similarity metric algorithm is organically combined in the detection algorithm. Flame detection uses dual band of infrared and visible light. Through the double determination of infrared and visible light, compared with the general image processing based flame recognition, the accuracy and stability of flame detection are improved. Smoke and fire detection program is developed on TMS320DM642 platform and video network transmission is achieved by i.MX27. The system has a good performance in different environments. It could well avoid disturbance of light and moving objects. The system has high real-time, quasi certainly and stability.

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“…A candidate block is declared as smoke block if the average probability of two RF classifiers in a smoke class is maximum. Surit and Chatwiriya (Surit, 2011) proposed a technique based on frame differencing. Moving blocks are examined and confirmed as smoke based on color.…”

Section: Improvements In Algorithms For Wildfire Smoke and Fire Detecmentioning

confidence: 99%

New generation of automatic ground based wildfire surveillance systems

Stipaničev¹,

Bugarić²,

Krstinić³

et al. 2014

Advances in Forest Fire Research

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A navegação consulta e descarregamento dos títulos inseridos nas Bibliotecas Digitais UC Digitalis, UC Pombalina e UC Impactum, pressupõem a aceitação plena e sem reservas dos Termos e Condições de Uso destas Bibliotecas Digitais, disponíveis em https://digitalis.uc.pt/pt-pt/termos.Conforme exposto nos referidos Termos e Condições de Uso, o descarregamento de títulos de acesso restrito requer uma licença válida de autorização devendo o utilizador aceder ao(s) documento(s) a partir de um endereço de IP da instituição detentora da supramencionada licença.Ao utilizador é apenas permitido o descarregamento para uso pessoal, pelo que o emprego do(s) título(s) descarregado(s) para outro fim, designadamente comercial, carece de autorização do respetivo autor ou editor da obra. Na medida em que todas as obras da UC Digitalis se encontram protegidas pelo Código do Direito de Autor e Direitos Conexos e demais legislação aplicável, toda a cópia, parcial ou total, deste documento, nos casos em que é legalmente admitida, deverá conter ou fazer-se acompanhar por este aviso. AbstractThe paper presents a state of the art in the research area of ground based wildfire surveillance systems with special emphasis on their latest generations proposed and developed in the last couple of years. We have focused primarily on novel, more efficient algorithms for wildfire detection, but other topics like fusion of video based systems with other wildfire detection systems and their integration with Geographic Information Systems (GIS) systems has also been analyzed. Our particular focus was on research carried out in our Department. Last but not least, we give our opinions and assumptions about future development of such systems.

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Forest Fire Smoke Detection in Video Based on Digital Image Processing Approach with Static and Dynamic Characteristic Analysis

Cited by 27 publications

References 4 publications

A survey on technologies for automatic forest fire monitoring, detection, and fighting using unmanned aerial vehicles and remote sensing techniques

A survey on technologies for automatic forest fire monitoring, detection, and fighting using unmanned aerial vehicles and remote sensing techniques

Networked Video Smoke and Fire Monitoring System Based on DM642 and i.MX27

New generation of automatic ground based wildfire surveillance systems

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