• Journal of the Semiconductor & Display Technology
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• v.10 no.2
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• pp.31-38
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• 2011

This paper introduces a video based traffic monitoring system for detecting vehicles and obstacles on the road. To segment moving objects from image sequence, we adopt the background subtraction algorithm based on the local binary patterns (LBP). Recently, LBP based texture analysis techniques are becoming popular tools for various machine vision applications such as face recognition, object classification and so on. In this paper, we adopt an extension of LBP, called the Diagonal LBP (DLBP), to handle the background subtraction problem arise in vision-based autonomous parking systems. It reduces the code length of LBP by half and improves the computation complexity drastically. An edge based shadow removal and blob merging procedure are also applied to the foreground blobs, and a pose estimation technique is utilized for calculating the position and heading angle of the moving object precisely. Experimental results revealed that our system works well for real-time vehicle localization and tracking applications.

• Journal of the Korean Society of Safety
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• v.28 no.1
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• pp.63-73
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• 2013

Dynamic strain history curve measured in the field is influenced by various factors such as vehicle type, speed, noise, temperature and running location etc.. Because such curve is used for vehicle weight estimation methodology suggested by Moses, exact strain history curve is the most important thing for exact estimation of vehicle weight. In this paper, effect of such factors mentioned above is investigated on the measured strain history curves, and results of weight estimation of vehicles are discussed quantitatively. From this study, it was known that temperature effect contained in the strain history curve measured for long time in-site gives the biggest effect on result of weight estimation and it can be removed by using the mode value. Furthermore, gross vehicle weight can be estimated within 5% error corresponding to A class of the European classification if effects of temperature and noise are removed and vehicle properties such as speed, axle arrangement and running location are considered properly.

• International Journal of Automotive Technology
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• v.7 no.3
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• pp.361-367
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• 2006

This paper describes a novel stereo vision based localization of free parking site, which recognizes the target position of automatic parking system. Pixel structure classification and feature based stereo matching extract the 3D information of parking site in real time. The pixel structure represents intensity configuration around a pixel and the feature based stereo matching uses step-by-step investigation strategy to reduce computational load. This paper considers only parking site divided by marking, which is generally drawn according to relevant standards. Parking site marking is separated by plane surface constraint and is transformed into bird's eye view, on which template matching is performed to determine the location of parking site. Obstacle depth map, which is generated from the disparity of adjacent vehicles, can be used as the guideline of template matching by limiting search range and orientation. Proposed method using both the obstacle depth map and the bird's eye view of parking site marking increases operation speed and robustness to visual noise by effectively limiting search range.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.22 no.4
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• pp.65-74
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• 2014

Unmanned aerial vehicles(UAVs) refer to the aircraft which carries no human pilot and is operated under remote control or in autonomous operational mode. As the UAVs can perform the dull, dangerous and difficult missions, various kinds of UAVs with different sizes and weights have been developed and operated for both civil and military application. As the avionics and communication technology related to the UAVs are matured, the demand for the UAVs is dramatically increased. Therefore, It is important to develope airworthiness process and regulations of the UAVs to minimize related risk to the man and environment. This paper describes related regulations and classification of the small UAVs for different international airworthiness authorities. The analysis of the CS-LURS verses Stanag 4702 and Stanag 4703 can provide guidelines for the generation of the airworthiness certification criteria for the small UAVs in civil sector. This paper conducted kinetic impact energy analysis of the loss of the small UAVs control scenarios and of the very small UAVs under 66 joules. Based on the analysis, the energy impact analysis can be considered before the design certification approval for the small UAVs.

• Journal of the Institute of Convergence Signal Processing
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• v.4 no.3
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• pp.1-6
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• 2003

It is difficult to detect and to track the moving targets like tanks and diesel vehicles due to the variety of terrain and moving of targets. It is possible to be happened the aliasing conditions as the difficulty of antenna deployment in the complex environment like the battle fields. In this paper, we study the problem of detecting and tracking of moving targets which are emitting wideband signals under severe spatial aliasing conditions because of the sparse arrays. We developed a direction of arrival(DOA) estimation algorithm based on subband MUSIC(Multiple Signal Classification) method which produces high-resolution estimation. In this algorithm, the true bearings are invariant regardless of changes of frequency bands while the aliased false bearings vary. As a result, the proposed algorithm overcomes the aliasing effects and improves the localization performance in sparse passive arrays.

• Journal of Korean Society of Transportation
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• v.19 no.6
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• pp.161-170
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• 2001

Vehicle detection is the basic of traffic monitoring. Video based systems have several apparent advantages compared with other kinds of systems. However, In video based systems, shadows make troubles for vehicle detection. especially active shadows resulted from moving vehicles. In this paper a new method that combines background subtraction and edge detection is proposed for vehicle detection and shadow rejection. The method is effective and the correct rate of vehicle detection is higher than 98(%) in experiments, during which the passive shadows resulted from roadside buildings grew considerably. Based on the proposed vehicle detection method, vehicle tracking, counting, classification and speed estimation are achieved so that traffic information concerning traffic flow is obtained to describe the load of each lane.

• Journal of Auto-vehicle Safety Association
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• v.13 no.4
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• pp.53-59
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• 2021

According to the Korean Traffic Accident Analysis System (TAAS), more than 200,000 traffic accidents occur every year. Also, the statistics including auto insurance companies data show 1.3 million traffic accidents. In the case of TAAS, the types of traffic accidents are simply divided into four; frontal collision, side collision, rear collision, and rollover. However, more detailed information is needed to assess for advanced driver assist systems at intersections. For example, directional information is needed, such as whether the vehicle in the car accident way in a straight or a left turn, etc. This study intends to redefine the type of accident with the more clear driving direction and path by referring to the Negligence standards used in automobile insurance accidents. The standards largely divide five categories of car-to-car/motorcycle /pedestrian/cyclist, and highway, and the each category is classified into dozens of types by status of the traffic signal, conflict situations. In order to present more various accident types for auto insurance accidents, the standards are reclassified driving direction and path of vehicles from crash situations. In results, the car-to-car accidents are classified into 33 accident types, car-to-pedestrian accidents have 19 accident types, car-to-motorcycle accidents have 38 accident types, and car-to-cyclist accidents are derived into 26 types.

• Journal of Platform Technology
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• v.8 no.1
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• pp.3-9
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• 2020

In Korea, 63% of the nation's land is made up of forests, and the average temperature of the earth has been increasing. Forest service has been operating a proactive control system for preventing the spread of forest pests such as Pine wilt disease. but there were some hurdles in timely control due to weather, topography and manpower management difficulties. In this paper, we propose a model for building fast, accurate and efficient control system by categorizing the damage and dead wood automatically based on the images acquired using small unmanned aerial vehicles based on information and communication technology. In particular, the proposed model establishes an effective response system for government affairs through cooperation in the private sector. It can also create new jobs in the unmanned aerial vehicle business and service industries.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.6
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• pp.1229-1236
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• 2022

In this paper, we studied accident-aware smart streetlights to prevent secondary accidents when driving on highways. It used Arduino and sensors to inform drivers of weather conditions, incorporated functions such as LED brightness control according to sunlight and night driving vehicles, and used Raspberry Pi camera OpenCV to learn various traffic accidents, natural disasters, and wildlife.

• Proceedings of the Korea Information Processing Society Conference
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• 2021.11a
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• pp.791-794
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• 2021

범죄차량 판독 시스템, 지능화된 CCTV 등 차량과 관련된 시각지능에 관한 연구가 큰 관심을 받고 있다. 이 중 차량 분류 기술은, 특정 차량을 인식하는 핵심기술이다. 이와 관련한 기존 연구들은 큰 차종으로만 분류하거나, 분류 가능한 차종의 수, 정확도 등이 낮아 실용성 및 신뢰성이 떨어진다는 단점이 있다. 따라서, 본 논문에서는 차종을 정확하게 분류할 수 있는 2단계 차종 분류 알고리즘을 제안한다. 제안 시스템은 CNN으로 학습된 모델을 기반으로 1차로 차량의 유형을 분류하고, 2차로 정확한 차종을 분류한다. 실험 결과, 52개의 차종을 분류함에 있어 단일 분류 모델에 비해 5.3%p 더 높은 90.2%의 분류 정확도를 보였다. 이를 통해, 더욱 정확한 차종 분류가 가능하다.