• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.1
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• pp.475-481
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• 2014

Recently, it is used to apply various improved methods to determine the cause of traffic accidents. However, most of vehicle black box usually start to store the video information by an event trigger in case that the impact value at that time exceeds the threshold impact value as compared the threshold impact value saved in advance with the current impact value. there are problems with above method that a lot video information should be saved in the memory card of the vehicle black box, and the user should delete the unwanted video information every time because of unclassified video store. In this paper, we propose the ontology-based context aware algorithm that the vehicle black box recognize the situation, and then remove the video data with a low weighting factor by itself for efficient memory management.

• 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.

• 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.

• 발명특허
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• v.32 no.1 s.366
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• pp.56-57
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• 2007

• 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.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.8
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• pp.1018-1023
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• 2019

Since 2010, vehicle black boxes have become popular with many people, if there is no record of the vehicle accident scene, or if the offender deliberately deletes the image data, the victim succeeds. The biggest advantage of blockchain is that it is impossible to modify and delete data by data distribution storage. The biggest disadvantage is that sensitive data is also distributed. In this paper, we propose a blockchain method for the black box by using the advantage of shared block data and we intend to solve the problem of personal information leakage which is a disadvantage of blockchain by storing sensitive information stored in a blockchain in a private server by LINK blockchain with a private server. We also attached code(Github) and demonstration video(Youtube) linking LINK blockchain with the private server in this paper.

• Proceedings of the Korea Information Processing Society Conference
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• 2012.11a
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• pp.841-843
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• 2012

본 논문에서는 안드로이드 기반의 태블릿 PC 환경에서 차량사고 발생 시 번호판 인식을 통하여 해당 사건의 증인을 확보 할 수 있는 증인 확보용 블랙박스 시스템을 제안한다. 이 방법은 기존의 블랙박스 기능에 추가적으로 영상에서 추출한 자동차들의 번호판을 인식하여 번호판 정보를 로그데이터로 저장하는 방식을 사용한다. 이로 인해 차량 사고에 대한 증인을 확보할 수 있는 시스템을 제공함으로써 사건에 대한 사용자의 불리한 입장을 완화 시켜줄 수 있는 객관적 데이터를 제공 및 저장하는 것을 목표로 한다.

• International Journal of Highway Engineering
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• v.11 no.1
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• pp.69-83
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• 2009

According to the accident statistics of 2006, it can be recognized that drivers' characteristics and driving behaviors are the most causational factors on the traffic accidents. At present, many recording tools such as digital speedometer or black box are distributed in the market to meet social requests of decreasing traffic accidents and increasing safe driving behaviors. However, it is also true that the system preventing any possible vehicle accidents in advance has not been developed. In this study, we developed critical value for deciding dangerous driving behaviors. The developed critical value could be used to contribute to safety driving management systematization and safety driving behaviors.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.11
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• pp.2423-2428
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• 2010

The number of motor vehicle registrations in Korea is increasing steadily each year, driven by industry development and economic growth. The number of traffic accidents is also rapidly increasing. Korea has a relatively high number of traffic accidents among OECD member countries, and it ranks among the highest in traffic accident death rates. This death rate is higher compared to death rates as a proportion of the number of traffic accidents in each country. It is very common for drivers to lose consciousness in traffic collisions, which leads to a failure to carry out early emergency measures. In order to prevent such situations as well as hit-and-runs and people left uncared for after traffic accidents, there is a need for motor vehicle black boxes and accident report systems. This study addressed the need for an emergency evacuation system for people injured in traffic accidents and a secondary traffic accident prevention system by developing a motor vehicle emergency situation detection and report system combined with a black box, and materializing it as an actual system.

• Proceedings of the Korean Information Science Society Conference
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• 2007.10b
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• pp.308-312
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• 2007

최근 차량용 블랙박스는 단순히 차속 및 주행 거리를 기록하는 차량 운행 기록기의 기능을 넘어, 각종 센서 및 영상 처리, GPS 장치 등을 통하여 수집된 정보를 토대로 자동차 사고 분석이나 부품 결함을 발견할 수 있는 기능을 추가 하는 것을 목표로 하고 있다. 본 논문은 자동차로부터 얻을 수 있는 정보를 다각도로 분류해 보고 자동차 사고 중 가장 놓은 비율을 차지하고 있는 차대차 사고재현을 위한 필수적인 파라미터를 선정함으로써 제한된 프로세싱 자원 하에서 사고 재현 효과를 극대화 할 수 있는 영상 블랙박스 모델을 제안하고 수집된 파라미터의 분석 절차를 제시한다.