• Proceedings of the Korean Information Science Society Conference
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• 2006.10b
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• pp.499-504
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• 2006

터널 내 화재 발생 시 대규모의 인명, 재산 피해가 발생하는데 이러한 상황을 조기에 탐지함으로써 피해를 최소화하기 위한 시스템이 필요하다. 또한 터널 내 설치된 CCTV를 사람이 24시간 감시하기에는 너무 어려운 점이 많다. 이에 따라 적절한 영상 처리를 통한 화염 및 연기 검출 시스템을 통해 경보를 알려줄 경우, 보다 편리하고 사람이 모니터 앞에 없을 때 화재 발생 시 화재를 검출할 수 있어 피해를 최소화 할 수 있다. 본 논문에서는 영상처리 기법을 이용하여 터널 안에서 발생한 화재 및 연기를 고속으로 탐지하기 위한 알고리즘을 제안하였다. 터널 안에서의 화재 탐지는 차량 조명 및 터널내의 조명등과 같은 여러 가지 상황에 의해 산불 탐지 알고리즘과 다른 독자적인 알고리즘의 개발이 요구된다. 본 논문에서 제시한 두 가지 알고리즘은 기존 알고리즘보다 정확한 위치 탐지와 초기 단계에서의 탐지가 가능하도록 되었다. 또한 우리는 실험 결과를 통해 각각의 성능을 비교함으로써 제시한 알고리즘의 타당성을 보여주었다.

• Journal of Digital Convergence
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• v.13 no.4
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• pp.377-385
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• 2015

The purpose of the study was to perform trend analysis of the exercise content i.e. element difficulty distribution scores, element group distribution scores obtained by the athletes during 2014 Korea Cup International Gymnastic finals. The conclusion drawn from the analysis are as follows: Firstly in terms of tournament technical difficulty value, Korean athletes showed characteristics of reliance on swing element rather than strength hold element which could actually secure higher difficulty scores. Secondly, skill acquisition of higher difficulty value is demanded by taking advantage of familiar characteristics from the swing element i.e. Jonasson and Roll bwd. Slowly with str. arms and body to swallow (2s.). Thirdly, development of sensory training and strengthening exercise program are essential to enhance strength hold technique.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.497-498
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• 2018

In the fire scene, it is difficult to see 1m ahead because of power failure, smoke and toxic gas, even with thermal imaging camera and Xenon searchlight. Analysis of the smoke particles in the fire scene shows that even if the smoke is $5{\mu}m$ or less in wavelength, it is difficult to obtain a front view when using a conventional thermal imaging camera if the visual distance exceeds 1 meter. In the case of black smoke with a particle wavelength of $5{\mu}m$ or more, a space permeation sensor technology using various sensors other than a single sensor is required because chemical materials, gas, and water molecules are mixed. Firefighters need a smoke detection technology for smoke detection and spatial information visualization for forward safety view.In this paper, we design the interface of the information processing system with 32bit CPU core and peripheral circuit. We also implemented and simulated the interface with Lidar sensor. Through this, we provide interface that can implement information processing system of human enhancement fire helmet in the future.

• Journal of Digital Convergence
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• v.16 no.12
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• pp.619-624
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• 2018

The purpose of this study was to examine the trend of men's gymnastics on floor exercise final(8 gymnasts) in the 2018 Asian Games through digital video materials. Video recordings of floor exercise final were collected from the 2018 Asian Games. The cross-check with three international gymnastics judges on floor exercise final was analyzed. To fulfil the D-score, 8 gymnasts were the most performed backward saltos elements group(36 elements), forward salto with 1/1 turn(8 gymnasts), backward salto with 5/2 turn(8 gymnasts) and backward salto with 3/1 turn(8 gymnasts). The scores showd average the D score 6.0, E score 7.9, and connection values 0.25. To get a good results on floor exercise, gymnasts need to get a average the D score over 6.0, E score over 8.5, and connection values over 0.3.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.12
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• pp.1596-1603
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• 2018

Rapidly detecting and warning of fires is necessary for minimizing human injury and property damage. Generally, when fires occur, both the smoke and the flames are generated, so fire detection systems need to detect both the smoke and the flames. However, most fire detection systems only detect flames or smoke and have the disadvantage of slower processing speed due to additional preprocessing task. In this paper, we implemented a fire detection system which predicts the flames and the smoke at the same time by constructing a CNN model that supports multi-labeled classification. Also, the system can monitor the fire status in real time by using Grad-CAM which visualizes the position of classes based on the characteristics of CNN. Also, we tested our proposed system with 13 fire videos and got an average accuracy of 98.73% and 95.77% respectively for the flames and the smoke.

• The Journal of the Convergence on Culture Technology
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• v.9 no.5
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• pp.843-847
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• 2023

In this paper, we propose a model for detecting efficient fire identification to prevent fires that can lead to various industrial accidents, farmland and large forest fires, with the widespread use of various chemicals and flammable substances as modern technology advances. This paper presents an algorithm that can detect fire smoke in a high-efficiency and short time using images, and an algorithm based on SVM(Support Vector Machine) and K fold cross-verification technologies. By analyzing images, fire and smoke detection algorithms have relatively superior detection performance compared to existing algorithms, and the analysis of fire and smoke characteristics detected in this paper is analyzed stably and efficiently and is expected to be used in various fields that may be exposed to fire risks in the future.

• Korea Multimedia Society
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• v.4 no.3
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• pp.83-90
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• 2000

• Korean Journal of Remote Sensing
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• v.38 no.5_3
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• pp.967-977
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• 2022

The occurrence and intensity of wildfires are increasing with climate change. Emissions from forest fire smoke are recognized as one of the major causes affecting air quality and the greenhouse effect. The use of satellite product and machine learning is essential for detection of forest fire smoke. Until now, research on forest fire smoke detection has had difficulties due to difficulties in cloud identification and vague standards of boundaries. The purpose of this study is to detect forest fire smoke using Level 1 and Level 2 data of Geostationary Environment Monitoring Spectrometer (GEMS), a Korean environmental satellite sensor, and machine learning. In March 2022, the forest fire in Gangwon-do was selected as a case. Smoke pixel classification modeling was performed by producing wildfire smoke label images and inputting GEMS Level 1 and Level 2 data to the random forest model. In the trained model, the importance of input variables is Aerosol Optical Depth (AOD), 380 nm and 340 nm radiance difference, Ultra-Violet Aerosol Index (UVAI), Visible Aerosol Index (VisAI), Single Scattering Albedo (SSA), formaldehyde (HCHO), nitrogen dioxide (NO₂), 380 nm radiance, and 340 nm radiance were shown in that order. In addition, in the estimation of the forest fire smoke probability (0 ≤ p ≤ 1) for 2,704 pixels, Mean Bias Error (MBE) is -0.002, Mean Absolute Error (MAE) is 0.026, Root Mean Square Error (RMSE) is 0.087, and Correlation Coefficient (CC) showed an accuracy of 0.981.

• The Journal of the Convergence on Culture Technology
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• v.5 no.2
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• pp.233-238
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• 2019

The purpose of this study was to realize and apply Taekwondo's technology and the fact that actors on stage and screen have much in common. In the meantime, there have been many prior studies on the development of the theoretical field. However, there is a slight lack of practical development and development plans, and it is time to improve. This seems to be a lack of practical experience leading to the creation of physical images. In that sense, I think that it should be supported by the complement of concrete and detailed research that seeks to make changes in open technology significantly. Considering this situation, it is necessary to further develop the practical field in parallel with the theoretical field. Therefore, I suggested the principle of physical behavior through Taekwondo technology and the development of acting skill. The performance training using these taekwondo techniques is meaningful research.

• Korean Journal of Remote Sensing
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• v.39 no.5_2
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• pp.859-873
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• 2023

Wildfires cause a lot of environmental and economic damage to the Earth over time. Various experiments have examined the harmful effects of wildfires. Also, studies for detecting wildfires and pollutant emissions using satellite remote sensing have been conducted for many years. The wildfire product for the Geostationary Environmental Monitoring Spectrometer (GEMS), Korea's first environmental satellite sensor, has not been provided yet. In this study, a false-color composite for better expression of wildfire smoke was created from GEMS and used in a U-Net model for wildfire detection. Then, a classification model was constructed to distinguish yellow dust from the wildfire smoke candidate pixels. The proposed method can contribute to disaster monitoring using GEMS images.