• Title/Summary/Keyword: Black-box camera

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A Study on the Fire Risk of Black Box Wiring in Motor Vehicle (자동차의 블랙박스 와이어링 화재 위험성에 관한 연구)

  • Kang, Sin-Dong;Kim, Ju-Hee;Choi, Jun-Pyo;Kim, Jae-Ho
    • Journal of the Korean Society of Safety
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    • v.32 no.6
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    • pp.22-28
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    • 2017
  • According to the National Fire Data System (NFDS), more than 5,000 vehicle fires have occurred every year for the last 10 years. Vehicle fires are primarily caused by mechanical (breaking system and engine), electrical (wiring and battery), and chemical (oil and fuel gas leakage) problems. The electrical factor has increased with the installation of driver convenience equipment. For example, today, the black box is widely used to provide video data recording of motor vehicle accidents. The black box consists of a front camera, rear camera, and wires. The black box wires are directly connected to the junction box or fuse box from the start battery that operates to provide normal on power supplying for engine stop. It is extremely dangerous when the wires short circuit due to insulation aging, mechanical and electrical stress, etc. In this study, the black box wiring fire risk have been analyzed and investigated when the steady state and abnormal operations, and under the following conditions: wiring arrangements with a high temperature condition, insulation aging, poor contact, and short circuits. The results showed that black box wiring short circuits had a higher fire risk than the other fire hazard elements. To prevent fire hazards caused by black box wiring, the black boxes must be installed by qualified service personnel. Do not modify the wiring, remove the fuse and secure the wiring using cable ties or insulation tape.

Designed rear sensing black-box system using Kinect (Kinect를 이용한 후방 감지 블랙박스 시스템 설계)

  • Kim, Gyu-Hyun;Jang, Jong-Wook
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2013.05a
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    • pp.290-293
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    • 2013
  • Due to vehicle personal injury accident does not, and to analyze the cause and prevention of a variety of devices and technologies are coming out. Among other things, representative of the black box, and rear camera. Despite these advances in technology, and vehicle human injuries continue to occur. The reason for this is that the children, the negligence of the driver or the vehicle is in reverse when a person suddenly passed the back of the vehicle, or the rear of the existing detection system is properly detected was unable to. Therefore, In this paper, we want to design a black box to reveal the cause of the accident, using Kinect to prevent accidents, rear-view camera and rear integrated black box system.

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Real Time Pothole Detection System based on Video Data for Automatic Maintenance of Road Surface Distress (도로의 파손 상태를 자동관리하기 위한 동영상 기반 실시간 포트홀 탐지 시스템)

  • Jo, Youngtae;Ryu, Seungki
    • KIISE Transactions on Computing Practices
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    • v.22 no.1
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    • pp.8-19
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    • 2016
  • Potholes are caused by the presence of water in the underlying soil structure, which weakens the road pavement by expansion and contraction of water at freezing and thawing temperatures. Recently, automatic pothole detection systems have been studied, such as vibration-based methods and laser scanning methods. However, the vibration-based methods have low detection accuracy and limited detection area. Moreover, the costs for laser scanning-based methods are significantly high. Thus, in this paper, we propose a new pothole detection system using a commercial black-box camera. Normally, the computing power of a commercial black-box camera is limited. Thus, the pothole detection algorithm should be designed to work with the embedded computing environment of a black-box camera. The designed pothole detection algorithm has been tested by implementing in a black-box camera. The experimental results are analyzed with specific evaluation metrics, such as sensitivity and precision. Our studies confirm that the proposed pothole detection system can be utilized to gather pothole information in real-time.

Mirror vision for car Black box (자동차 블랙박스를 위한 미러 비전)

  • Kim, Eun-Ho;Lim, Myoung-Sub
    • Proceedings of the KIEE Conference
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    • 2007.04a
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    • pp.369-372
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    • 2007
  • about commercial business of car black box, mirror vision for car black box deal with analysis of Existing Car Black boxes in market to provide the objective information associated with surrounding scene of car instead of witness, we experimented on suitable structure of all direction to cover surrounding of car considering dead zone where can't see at short distance and realized simple structure of gathering scene using mirror and lens and by saving the number of camera and MUX of pre-circut

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Effective Road Distance Estimation Using a Vehicle-attached Black Box Camera (차량 장착 블랙박스 카메라를 이용한 효과적인 도로의 거리 예측방법)

  • Kim, Jin-Soo
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.19 no.3
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    • pp.651-658
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    • 2015
  • Recently, lots of research works have been actively focused on the self-driving car. In order to implement the self-driving car, lots of fusion techniques should be merged and, specially, it is noted that a vehicle-attached camera can provide several useful functionalities such as traffic lights recognition, pedestrian detection, stop-line recognition including simple driving records. Accordingly, as one of the efficient tools for the self-driving car implementation, this paper proposes a mathematical model for estimating effectively the road distance with a vehicle-attached black box camera. The proposed model can be effectively used for estimating the road distance by using the height of black box camera or the widths of the referenced road line and the observed road line. Through several simulations, it is shown that the proposed model is effective in estimating the road distance.

A License Plate Recognition Algorithm using Multi-Stage Neural Network for Automobile Black-Box Image (다단계 신경 회로망을 이용한 블랙박스 영상용 차량 번호판 인식 알고리즘)

  • Kim, Jin-young;Heo, Seo-weon;Lim, Jong-tae
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.22 no.1
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    • pp.40-48
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    • 2018
  • This paper proposes a license-plate recognition algorithm for automobile black-box image which is obtained from the camera moving with the automobile. The algorithm intends to increase the overall recognition-rate of the license-plate by increasing the Korean character recognition-rate using multi-stage neural network for automobile black-box image where there are many movements of the camera and variations of light intensity. The proposed algorithm separately recognizes the vowel and consonant of Korean characters of automobile license-plate. First, the first-stage neural network recognizes the vowels, and the recognized vowels are classified as vertical-vowels('ㅏ','ㅓ') and horizontal-vowels('ㅗ','ㅜ'). Then the consonant is classified by the second-stage neural networks for each vowel group. The simulation for automobile license-plate recognition is performed for the image obtained by a real black-box system, and the simulation results show the proposed algorithm provides the higher recognition-rate than the existing algorithms using a neural network.

Design Around Algorithm view Using wireless camera (무선 카메라를 이용한 어라운드 뷰 알고리즘 설계)

  • Kim, Gyu-Hyun;Jang, Jong-Wook
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2013.10a
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    • pp.466-469
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    • 2013
  • Cars that are currently available to the operator to ensure convenience and safety for electronics devices now on the market supply is developed. The current car black box of electronics service, parking, is to help when reversing. The black box is necessary at the time of the accident. After-market through a lot of these are advertised. However, these products are known only to the rear or the front of the picture, as well, at the time of driving, the accident and the front left and right lateral images of the boundary of the car can not be confirmed. Electronics devices on the market, but they can not give this problem solving. In this paper, we propose these to the algorithm-around view of the driver's operation of the vehicle after the car sideways, left and right of the room with integrated video Black Box is designed to provide.

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Design Android-based image processing system using the Around-View (안드로이드 기반 영상처리를 이용한 Around-View 시스템 설계)

  • Kim, Gyu-Hyun;Jang, Jong-Wook
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2014.05a
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    • pp.421-424
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    • 2014
  • Currently, car black box, and CCTV products, such as image processing are prevalent on the market giving convenience to users.In particular, the black box of the driver driving a vehicle accident that occurred at the time to help identify the cause of the accident is gaining. Black box, the front or rear of the vehicle can check the image only. Because of the angle of view of the driver's vision or the black box can not determine a non-scene. In order to solve this problem by a more advanced system, the black box AVM (Around-View Monitoring) systems have been developed. AVM system to the vehicle's top-view images obtained before and after, left and right of the image, ie, $360^{\circ}$ image of the vehicle can be secured. AVM system must be installed on the vehicle, a desktop that you can acquire images Cling conditions. In this paper, we propose an Android-based tablet using the AVM system of the vehicle can achieve a $360^{\circ}$ image you want to design the system.

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Implementation of a Black-Box Program Monitoring Abnormal Body Reactions (부정기적 발생 신체이상 모니터링 블랙박스 프로그램 구현)

  • Kim, Won-Jin;Yoon, Kwang-Yeol
    • The Journal of the Korea institute of electronic communication sciences
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    • v.7 no.3
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    • pp.671-677
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    • 2012
  • A black-box program was implemented in order to monitor abnormal symptoms of human body irregularly occurring during sleep. The system consists of sensor probing body signals, auxiliary devices such as the alarm, lamp, network camera, and signal monitoring computer. Various types of sensors, PPG, ECG, EEG, temperature, respiration sensor, G-sensor, and microphone were used to more exactly identify the causes of abnormal symptoms. If a symptom occurs, the system records the patient's condition to provide information being utilized in the treatment. The sensors are attached on some locations of body being proper to check a specific type of abnormal reaction. Based on the normal range and type of measurement data, criteria of signal levels were set to distinguish abnormal reaction. An abnormal signal being probed, the program starts to operate the lamp, alarm, and network camera at the same time and stores the signal and video data.

Traffic Lights Detection and Recognition System Using Black-Box Images (차량용 블랙박스 영상을 이용한 주간 신호등 탐지 및 인식 시스템)

  • Hawng, Ji-Eun;Ahn, Dasol;Lee, Seunghwa;Park, Sung-Ho;Park, Chun-Su
    • Journal of the Semiconductor & Display Technology
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    • v.15 no.2
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    • pp.43-48
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    • 2016
  • In this paper, we propose a traffic light detection and recognition (TLDR) algorithm in the daytime. The proposed algorithm utilizes the color and shape information for the TLDR. At first, a traffic light is detected and recognized based on its shape information. Then, the color range of the detected traffic light is investigated in HSV color space. The input data of the proposed TLDR algorithm is the color image captured using the black box camera during driving. Our simulations demonstrate that the proposed algorithm can achieve a high detection and recognition performance for the images including traffic lights.