• Title/Summary/Keyword: Fire image recognition

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Design of Intelligent Image recognition System by Pedestrian Recognition in the Fire (화재현장 보행자 인식을 통한 지능형 영상인식 시스템 설계)

  • Kim, Pyeong-Kang;Park, Seok-Cheon;Kim, Hyeong-Hun
    • Proceedings of the Korea Information Processing Society Conference
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    • 2013.11a
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    • pp.1551-1553
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    • 2013
  • 지능형 영상감시에 대한 연구와 개발이 가속화되면서, 화재감시에 대한 예방 및 경보시스템 또한 빠른 속도로 발전하고 있다. 그러나, 기존시스템은 화재에 대한 감시기능에만 국한되어 있어, 기능으로써의 한계점을 가지고 있다. 따라서 본 논문에서는 이러한 문제점을 해결하기위해, 본 논문에서는 화재와 보행자를 검출하여, 초기대응 및 화재원인에 대한 정보를 제공하며, 보행자에 대한 안전을 최대한 보장할 수 있는 화재현장 보행자 인식을 통한 지능형 영상인식 시스템을 설계하였다.

Flame and Smoke Detection for Early Fire Recognition (조기 화재인식을 위한 화염 및 연기 검출)

  • Park, Jang-Sik;Kim, Hyun-Tae;Choi, Soo-Young;Kang, Chang-Soon
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2007.10a
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    • pp.427-430
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    • 2007
  • Many victims and property damages are caused in fires every year. In this paper, flame and smoke detection algorithm by using image processing technique is proposed to early alarm fires. The first decision of proposed algorithms is to check candidate of flame region with its unique color distribution distinguished from artificial lights. If it is not a flame region then we can check to candidate of smoke region by measuring difference of brightness and chroma at present frame. If we just check flame and smoke with only simple brightness and hue, we will occasionally get false alarms. Therefore we also use motion information about candidate of flame and smoke regions. Finally, to determine the flame after motion detection, activity information is used. And in order to determine the smoke, edges detection method is adopted. As a result of simulation with real CCTV video signal, it is shown that the proposed algorithm is useful for early fire recognition.

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An Implementation of Automatic Transmission System of Traffic Event Information (교통이벤트 정보의 자동 전송시스템 구현)

  • Jeong, Yeong-Rae;Jang, Jae-Hoon;Kang, Seog Geun
    • The Journal of the Korea institute of electronic communication sciences
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    • v.13 no.5
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    • pp.987-994
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    • 2018
  • In this paper, an automatic transmission system of traffic information is presented. Here, a traffic event is defined as an obstacle to an emergency vehicle such as an ambulance or a fire truck. When a traffic event is detected from a video recorded by a black box installed in a vehicle, the implemented system automatically transmits a proof image and corresponding information to the control center through an e-mail. For this purpose, we realize an algorithm of identifying the numbers and a character from the license plate, and an algorithm for determining the occurrence of a traffic event. To report the event, a function for automatic transmission of the text and image files through e-mail and file transfer protocol (FTP) is also appended. Therefore, if the traffic event is extended and applied to the presented system, it will be possible to establish a convenient reporting system for the violation of various traffic regulations. In addition, it will contribute to significantly reduce the number of traffic violations against the regulations.

Image Restoration Network with Adaptive Channel Attention Modules for Combined Distortions (적응형 채널 어텐션 모듈을 활용한 복합 열화 복원 네트워크)

  • Lee, Haeyun;Cho, Sunghyun
    • Journal of the Korea Computer Graphics Society
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    • v.25 no.3
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    • pp.1-9
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    • 2019
  • The image obtained from systems such as autonomous driving cars or fire-fighting robots often suffer from several degradation such as noise, motion blur, and compression artifact due to multiple factor. It is difficult to apply image recognition to these degraded images, then the image restoration is essential. However, these systems cannot recognize what kind of degradation and thus there are difficulty restoring the images. In this paper, we propose the deep neural network, which restore natural images from images degraded in several ways such as noise, blur and JPEG compression in situations where the distortion applied to images is not recognized. We adopt the channel attention modules and skip connections in the proposed method, which makes the network focus on valuable information to image restoration. The proposed method is simpler to train than other methods, and experimental results show that the proposed method outperforms existing state-of-the-art methods.

Landslide Prediction with Angle of Repose Prediction Using 3D Spatial Coordinate System and Drone Image Detection (3차원 공간 좌표 시스템과 드론 영상 검출을 활용한 산사태 안식각 예측에 관한 연구)

  • Yong-Ju Chu;Soo-Young Lim;Seung-Yop Lee
    • Smart Media Journal
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    • v.12 no.3
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    • pp.77-84
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    • 2023
  • Forest fires are representative natural disasters resulting from dramatic global climate change in these modern times. When forest formation is insufficient due to forest damage caused by fire, secondary damages such as landslides occur during the winter thawing period and heavy rains. In most countries, only a limited area is managed as CCTV-centered monitoring systems for forest management. For the landslide prediction, markers containing 3D spatial coordinates were located on the slopes of the danger areas in advance. Then 3D mapping and angle of repose were obtained by periodic drone imaging. The recognition range and angle of view of markers were defined, and a new method for predicting signs of landslides in advance was presented in this study.

PID Controled UAV Monitoring System for Fire-Event Detection (PID 제어 UAV를 이용한 발화 감지 시스템의 구현)

  • Choi, Jeong-Wook;Kim, Bo-Seong;Yu, Je-Min;Choi, Ji-Hoon;Lee, Seung-Dae
    • The Journal of the Korea institute of electronic communication sciences
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    • v.15 no.1
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    • pp.1-8
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    • 2020
  • If a dangerous situation arises in a place where out of reach from the human, UAVs can be used to determine the size and location of the situation to reduce the further damage. With this in mind, this paper sets the minimum value of the roll, pitch, and yaw using beta flight to detect the UAV's smooth hovering, integration, and derivative (PID) values to ensure that the UAV stays horizontal, minimizing errors for safe hovering, and the camera uses Open CV to install the Raspberry Pi program and then HSV (color, saturation, Brightness) using the color palette, the filter is black and white except for the red color, which is the closest to the fire we want, so that the UAV detects the image in the air in real time. Finally, it was confirmed that hovering was possible at a height of 0.5 to 5m, and red color recognition was possible at a distance of 5cm and at a distance of 5m.

New Scheme for Smoker Detection (흡연자 검출을 위한 새로운 방법)

  • Lee, Jong-seok;Lee, Hyun-jae;Lee, Dong-kyu;Oh, Seoung-jun
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.41 no.9
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    • pp.1120-1131
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    • 2016
  • In this paper, we propose a smoker recognition algorithm, detecting smokers in a video sequence in order to prevent fire accidents. We use description-based method in hierarchical approaches to recognize smoker's activity, the algorithm consists of background subtraction, object detection, event search, event judgement. Background subtraction generates slow-motion and fast-motion foreground image from input image using Gaussian mixture model with two different learning-rate. Then, it extracts object locations in the slow-motion image using chain-rule based contour detection. For each object, face is detected by using Haar-like feature and smoke is detected by reflecting frequency and direction of smoke in fast-motion foreground. Hand movements are detected by motion estimation. The algorithm examines the features in a certain interval and infers that whether the object is a smoker. It robustly can detect a smoker among different objects while achieving real-time performance.

A model to secure storage space for CCTV video files using YOLO v3

  • Seong-Ik, Kim
    • Journal of the Korea Society of Computer and Information
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    • v.28 no.1
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    • pp.65-70
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    • 2023
  • In this paper, we propose a CCTV storage space securing model using YOLO v3. CCTV is installed and operated in various parts of society for disasters, disasters and safety such as crime prevention, fire prevention, and monitoring, and the number of CCTV is increasing and the quality of the video quality is improving. Due to this, as the number and size of image files increase, it is difficult to cope with the existing storage space. In order to solve this problem, we propose a model that detects specific objects in CCTV images using YOLO v3 library and deletes unnecessary frames by saving only the corresponding frames, thereby securing storage space by reducing the size of the image file, and thereby Periodic images can be stored and managed. After applying the proposed model, it was confirmed that the average image file size was reduced by 94.9%, and it was confirmed that the storage period was increased by about 20 times compared to before the application of the proposed model.

Identifiers Recognition of Container Image Using Morphological Characteristic and FCM-based Fuzzy RBF Networks (형태학적 특성과 FCM 기반 퍼지 RBF 네트워크를 이용한 컨테이너 식별자 인식)

  • Kim, Tae-Hyung;Soung, Won-Goo;Kim, Kwang-Baek
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2007.06a
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    • pp.252-257
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    • 2007
  • 우리나라의 항만은 수 출입화물의 99.5%를 처리하며, 육로 및 철도 수송 물동량의 기종점 역할을 수행하는 중요한 곳으로서 항만 물동량의 신속한 처리와 자동화 시스템에 의한 비용절감은 엄청난 효과를 가져온다. 따라서 본 논문에서는 항만에서 취급하는 컨테이너를 자동으로 식별할 수 있는 자동화 방법을 제안한다. 실제 컨테이너 영상을 그레이 영상으로 변환한 후, 프리윗 마스크(Prewitt-Mask)를 적용하여 윤곽선을 추출하고 컨테이너를 식별할 수 있는 개별 식별자의 형태학적 특징 정보를 이용하여 식별자 후보영역을 검출한다. 검출된 식별자 후보영역은 개별 식별자 영역외에 잡음 영역이 포함되어 있으므로 4방향 윤곽선 추적 알고리즘과 Grassfire 알고리즘을 적용하여 잡음을 제거하고 개별 식별자들을 각각 객체화한다. 잡음이 제거된 식별자 후보 영역에서 객체화 한 개별 식별자는 컨테이너 식별을 위해 FCM 기반 퍼지 RBF 네트워크를 적용하여 인식한다. 본 논문에서 제안한 컨테이너 식별자 인식 방법의 성능을 평가하기 위해 실제 컨테이너 영상 300장을 대상으로 실험한 결과, 기존의 방법보다 인식 성능이 개선되었음을 확인할 수 있었다.

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Analysis on Factors of Importance and Performance in terms of Securing Customers of Farm Restaurants - Based on the Case of Bibijeong in Wanju-Gun - (농가레스토랑 이용고객의 중요도-만족도 분석 - 완주군 비비정을 사례로 -)

  • Han, A-Reum;Han, Jin;Lee, In-Jae;Jang, Dong-Heon
    • Journal of Korean Society of Rural Planning
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    • v.21 no.2
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    • pp.163-175
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    • 2015
  • This study aimed to analyze factors of importance and performance picked by customers of Bibijeong, a farm restaurant operated by the local community of Wanju-gun. Major points include: Recognition paths mostly were word of mouth and mass media, types of visit were in the company of friends, family members or work colleagues, and purposes of visit included consumption of meal and identifying features of the restaurant. Secondly, factor analysis showed that level of facility, atmosphere/cleanness, diversity of menu, employees, ingredients and network. The Cronbach Alpha coefficient was +0.6. Thirdly, average of importance of factors was 3.861 while average performance was 3.429. IPA analysis showed that employee(communication, customer contact) in the first quadrant proved the need for fast improvement through training. Atmosphere/cleanness (interior atmosphere, table clean, kitchen cleanliness, clean dishes, interion design) and employee(proficiency, menu recognition), foodstuff(freshness, origin, safety) in the second quadrant showed that the marketing strategy of improvement as well as maintaining current status is needed, including regular training and hygiene inspection. The third quadrant contains facilities(disability, baby, fire protection) and food menu(food packing, various menu, creative menu, menu description), network(village economic links), which showed the need for gradual improvement. The forth quadrant contains network(sights's near contains. The results so far can be summed into the statement that overcoming the basic functionality of providing meals and linking the restaurant with local attractions and local economy would be need, as well as building up the image of unique farm restaurant with local features, so that Bibijeong can serve as the centerpiece of community and foundation of exchange with other areas.