• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.5
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• pp.171-182
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• 2019

Bicycles are a pollution-free means of transportation. In addition to leisure, the use of bicycles is increasing as alternative eco-friendly transportation. Accordingly, bicycle accidents are also increasing. The purpose of this study is to implement bicycle black box technology to identify situation when a bicycle accident occurs. Currently, bicycle black box products are mainly based on video cameras, and are commercially available by adding various functions mainly on high resolution cameras and are sold at high prices. If a bicycle accident occurs, quantitative data on the accident location at the time of the accident and the state of the bicycle at the time of the accident is required. In this study, IMU sensor used to obtain acceleration and slope, and time and coordinates are obtained. In addition, real-time acceleration and tilt data while is stored in memory card and by using Bluetooth transmit to the smart phone owned by the in real time to prevent accidents and to monitor status.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.22 no.4
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• pp.771-783
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• 2012

This paper proposes a scheme to collect video data of the vehicle black box in order to strengthen the public safety. The existing schemes, such as surveillance system with the fixed CCTV and car black box, have privacy issues, network traffic overhead and the storage space problems because all video data are sent to the central server. In this paper, the central server only collects the video data related to the accident or the criminal offense using the GPS information and time in order to investigation of the accident or the criminal offense. The proposed scheme addresses the privacy issues and reduces network traffic overhead and the storage space of the central server since the central server collects the video data only related to the accident and the criminal offense. The implementation and experiment shows that our service is feasible. The proposed service can be used as a component of remote surveillance system to prevent the criminal offense and to investigate the criminal offense.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.241-244
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• 2018

Domestic vehicle registration is continuously increasing every year, traffic accidents are also increasing by an increase in the number of vehicles. In the event of a traffic accident, the perpetrator and the victim should be judged and handled appropriately. When judging the accident situation, the black box is what evidence can be except for witness who is at the accident scene. The black box becomes an essential role in order to prevent traffic accidents. However, there is no way to prove integrity by evidence corruption, fabrication and etc. For this reason, we propose a method to guarantee the integrity of image through hash value generated by using PingPong 256 encryption algorithm for integrity verification in this paper.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.5
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• pp.747-753
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• 2018

In the license-plate recognition systems for automobile black Image, the license-plate image frequently has a shadow due to outdoor environments which are frequently changing. Such a shadow makes unpredictable errors in the segmentation process of individual characters and numbers of the license plate image, and reduces the overall recognition rate. In this paper, to improve the recognition rate in these circumstance, a license-plate image binarization algorithm is proposed removing the shadow effectively. The propose algorithm splits the license-plate image into the regions with the shadow and without. To find out the boundary of two regions, the algorithm estimates the curve for shadow boundary using the least-squares method. The simulation is performed for the license-plate image having its shadow, and the results show much higher recognition rate than the previous algorithm.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.8
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• pp.2942-2950
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• 2010

Car black box helps to investigate the cause of accident by recording time, position and videos as well as shock information. In addition, the car black box need a function to support safe driving for preventing accident. The representative driving support function is a lane departure warning. In order to implement the function, it is necessary to carry out the image processing to detect the lane first. The image processing algorithm requires computational burden to handle so much data and complicated structure of algorithm. This paper describes the efficient image processing algorithm with relatively low amount of computation for car black box embedded platform to detect lanes from the real-time lane image.

• Proceedings of the Korea Information Processing Society Conference
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• 2022.05a
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• pp.441-442
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• 2022

교통사고 예측은 차량의 블랙박스 동영상을 통해 사고 발생을 최대한 빨리 예측하는 것을 목표로 한다. 이는 안전한 자율주행 시스템을 보장하는 데 중요한 역할을 한다. 다양한 교통 상황과 카메라의 제한된 시야로 인해 프레임에서 사고 가능성을 조기에 관찰하는 것은 어려운 도전이다. 예측의 핵심 기술은 객체의 시공간 관계를 학습하는 것이다. 본 논문에서는 블랙박스 동영상에서 사고 예측을 위한 계산 모델을 제안한다. 이것을 사용하여 사고 예방을 강화한다. 이 모델은 사고 위험에 대한 운전자의 시각적 인식에서 영감을 받았다. 객체 탐지기는 동영상 프레임에서 다양한 객체를 탐지한다. 탐지한 객체는 노드 생성기와 특징 추출기 동시에 통과한다. 노드 생성기에서 생성한 노드는 GCN 실행기를 사용한다. GCN 실행기는 각 프레임에 대한 객체의 3D 위치 관계를 계산한 후 공간 특징을 취득한다. 동시에 공간 특징과 특징 추출기에서 얻은 객체의 특징은 GRU 실행기로 보내진다. GRU 실행기 안에 시공간 특징을 암기하고 분석하여 교통사고 확률을 예측한다.

• Review of KIISC
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• v.24 no.2
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• pp.21-27
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• 2014

사용자의 편리함과 유익함 뒤에는 높은 위험성이 공존한다. 특히 자동차의 경우에는 빠른 속도로 장소를 이동할 수 있다는 장점이 있지만, 사고 발생 시에 생명을 위협할 만큼의 위험을 가지고 있다. 자동차 사고 발생 후에는 시시비비를 가리기 위해서 많은 분쟁이 발생하는 것이 일반적인 판례였다. 자동차용 블랙박스는 자동차 사고 발생 시에 정확한 현장의 영상, 음성 및 기타 센서 정보를 기록한다. 이를 이용해서 전후좌우, 차량의 상태를 분석하여 사건 발생의 실마리를 찾을 수 있는 중요한 단서로 사용된다. 하지만, 아직은 블랙박스 영상만으로는 법적인 자료로 사용될 수는 없다. 즉, 법적인 자료로 채택되기 위한 기밀성과 무결성 측면에서 약점을 가지고 있다. 이에 따라서 기록된 정보를 암호화하고, 접근 자에 대한 기록을 남기는 기능이 연구 및 표준화 제정되고 있다. 차량 내외에서 수집된 정보에 암호화를 적용하여 이종 기기간 데이터 공유를 차단하고, 자동차 정보기기 보안 인증서를 가지고 있는 단체를 통하여 보안키를 이용하여 정보를 활용하기 위한 시스템이 구성되고 있다. 이를 통하여 자동차 융합 정보통신 장치들로부터 기록된 정보를 법적인 객관적 근거로 활용할 수 있도록 자동차용 정보통신 기기들이 기밀성과 무결성을 준수할 수 있도록 발전할 것이다.

• 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.

• 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.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.2
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• pp.133-146
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• 2023

Traffic states in urban areas are essential to implement effective traffic operation and traffic control. However, installing traffic sensors on numerous road sections is extremely expensive. Accordingly, estimating the traffic state using a vehicle-mounted camera, which shows a high penetration rate, is a more effective solution. However, the previously proposed methodology using object tracking or optical flow has a high computational cost and requires consecutive frames to obtain traffic states. Accordingly, we propose a method to detect vehicles and lanes by object detection networks and set the region between lanes as a region of interest to estimate the traffic density of the corresponding area. The proposed method only uses less computationally expensive object detection models and can estimate traffic states from sampled frames rather than consecutive frames. In addition, the traffic density estimation accuracy was over 90% on the black box videos collected from two buses having different characteristics.