• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.93-96
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• 2015

In this paper, we introduce a fire detection system using context-aware sensor. In existing weather and based on vision sensor of fire detection system case, acquired image through sensor of camera is extracting features about fire range as processing to convert HSI(Hue, Saturation, Intensity) model HSI which is color space can have durability in illumination changes. However, in this case, until a fire occurs wide range of sensing a fire in a single camera sensor, it is difficult to detect the occurrence of a fire. Additionally, the fire detection in complex situations as well as difficult to separate continuous boundary is set for the required area is difficult. In this paper, we propose an algorithm for real-time by using a temperature sensor, humidity, Co2, the flame presence information acquired and comparing the data based on multiple conditions, analyze and determine the weighting according to fire it. In addition, it is possible to differential management to intensive fire detection is required zone dividing the state of fire.

• Journal of IKEEE
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• v.23 no.1
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• pp.242-248
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• 2019

Fire flame and smoke detection algorithm studies are challenging task in computer vision due to the variety of shapes, rapid spread and colors. The performance of a typical sensor based fire detection system is largely limited by environmental factors (indoor and fire locations). To solve this problem, a deep learning method is applied. Because it extracts the feature of the object using several methods, so that if a similar shape exists in the frame, it can be detected as false postive. This study proposes a new algorithm to reduce false positives by using frame similarity before using deep learning to decrease the false detection rate. Experimental results show that the fire detection performance is maintained and the false positives are reduced by applying the proposed method. It is confirmed that the proposed method has excellent false detection performance.

• Journal of Korean Association for Spatial Structures
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• v.10 no.2
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• pp.135-145
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• 2010

The objective of this study is to draw basic data for the application of the fire protection planning for the future plan large enclosure buildings in Korea through an analysis of its characteristics by case studies of the domestic and foreign large scale gymnasiums. In this study, domestic building codes for the fire protection are investigated and fire detection systems, fire extinguishing systems, smoke control systems and evacuation systems of three large scale gymnasiums located at Korea and eight foreign countries are compared and analyzed. The results of this study show that infrared light fire detection system and flame detector for spacial characteristics are potentially used in fire protection systems of large scale gymnasiums: dry type sprinkler and sprinkler water gun are adopted in fire detection system; and smoke accumulation system is widely utilized in smoke control system.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.4
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• pp.59-70
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• 2008

In this paper, we proposed image processing technique for automatic real-time fire and smoke detection in tunnel environment. To avoid the large scale of damage of fire occurred in variety environments, it is purposeful to propose many studies to minimize and to discover the incident as fast as possible. But we need new specific algorithm because tunnel environment is quite different and it is difficult to apply previous fire detection algorithm to tunnel environment. Therefore, in this paper, we proposed specific algorithm which can be applied in tunnel environment. To minimize false detection in tunnel we used color and motion information. And it is possible to detect exact position in early stage with detection, test, verification procedures. In addition, by comparing properties of each algorithm throughout experiment, we have proved the validity and efficiency of proposed algorithm.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.49 no.1
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• pp.63-73
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• 2021

This paper presents a algorithm for automatic target recognition robust to the influence of the flame in order to track the target by EOTS(Electro-Optical Targeting System) equipped on UAV(Unmanned Aerial Vehicle) when there is aerial target or marine target with flame at the same time. The proposed method converts infrared images of targets and flames into a gradient vector field, and applies each gradient magnitude to a polynomial curve fitting technique to extract polynomial coefficients, and learns them in a shallow neural network model to automatically recognize targets and flames. The performance of the proposed technique was confirmed by utilizing the various infrared image database of the target and flame. Using this algorithm, it can be applied to areas where collision avoidance, forest fire detection, automatic detection and recognition of targets in the air and sea during automatic flight of unmanned aircraft.

• Journal of the Korea Safety Management & Science
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• v.16 no.4
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• pp.379-389
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• 2014

Fire detectors are designed to minimize loss of life from a fire alarm system as an alarm to help evacuate more quickly until the completion of the evacuation alarm should be continued. the purpose of such alarms in order to achieve the characteristic fire heat release rate reaches a certain level, or when a certain time has elapsed, when the heat detector is to be alarms to answer. Requires a quick response, it is desirable to install the sensor as much as possible, but taking into account the cost of installation problems by engineering approach to minimize the quantity and rapidity of detection capability should be increased. In order to increase the rapidity of fire detectors in a room according to the height of the sensing period is to be maintained the optimum distance of the fire detector detects characteristics should be considered. Differential spot-type heat detectors installed domestic basis, depending on the type of sensor that can detect one sensor area is limited and less than 4m ceiling height regulations and simply double the number in excess of 4m and intended to be installed.

• The Journal of the Korea Contents Association
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• v.13 no.6
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• pp.40-47
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• 2013

In case of wild fire, early detection of wild fire is the most important factor in minimizing the damages. In this paper, we suggest an effective system that detects wild fire using a panoramic image from a single camera with PAN/TILT head. This enables the system to detect the size and the location of the fire in the early stages. After converting RGB image input to color YCrCb image, the differential image is used to detect changes in movement of the smoke to determine the regions which may be prone to forest fire. Histogram analysis of fire flame is used to determine the possibility of fire in the predetermined regions. In addition, image matching and SURF were used to create the panoramic image. There are many advantages in this system. First of all, it is very economical because this system needs only a single camera and a monitor. Second, it shows the live image of wide view through panoramic image. Third, this system can reduce the quantity of saved data by storing panoramic images.

• The Journal of the Korea institute of electronic communication sciences
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• v.6 no.2
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• pp.206-211
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• 2011

In this paper, a fire detection algorithm based on video processing is proposed. At the first stage, background image extracted from CCTV video input signal, and then foreground image were separated by differencing CCTV input signal from background image. At the second stage, candidated area were extracted by using color information from foreground image. At the final stage, smoke or flame characteristic area were separated by using Gaussian mixture modeling applied to candidated area, and then fire can be detected. Through real experiments at the inner room, it is shown that the proposed system works well.

• Fire Science and Engineering
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• v.23 no.2
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• pp.1-5
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• 2009

We studies wish to investigated establishment form of cabinet board, and confirm possibility of electrical disaster prevention through reappearance experiment of odor detection system. Established breaker consists of MCCB, RCD order in cabinet board for house, but industry is used together with. When imposed shock using shaker to terminal block that contact becomes in appropriate, flame was made sure. According to result that experiment attaching odor capsule in terminal block, capsule commissioned exactly by occurred heat. According to establishment position of sensor, difference of inspection time was about 10 seconds. Estimate odor inspection system by thing which electrical device accident prevention is available. When there is abnormal generated heat in connection of electric wire, accident prevention estimates that is possible by giving an alarm state of overheat to administrator.

• Journal of IKEEE
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• v.22 no.4
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• pp.1079-1087
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• 2018

Recently, computer vision field based deep learning artificial intelligence has become a hot topic among various image analysis boundaries. In this study, flames are detected in fire images using the Faster R-CNN algorithm, which is used to detect objects within the image, among various image recognition algorithms based on deep learning. In order to improve fire detection accuracy through a small amount of data sets in the learning process, we use image augmentation techniques, and learn image augmentation by dividing into 6 types and compare accuracy, precision and detection rate. As a result, the detection rate increases as the type of image augmentation increases. However, as with the general accuracy and detection rate of other object detection models, the false detection rate is also increased from 10% to 30%.