• 한국멀티미디어학회논문지
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• 제8권11호
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• pp.1449-1461
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• 2005

본 논문에서는 차량의 식별마크 분류 및 차량번호판 인식을 통한 차량인식 알고리즘을 제안하였다. 제안한 알고리즘에서는 먼저 입력 차량영상으로 부터 잡음제거, 세선화 과정 등 전처리 과정들을 수행하고 명암값 변화 빈도 분포를 사용하여 차량식별마크와 번호판 영역을 추출하였다. 또한 추출된 후보 영역으로부터 차량 식별마크와 번호판 영역의 구조적 특성 정보를 사용하여 차량 식별마크, 번호판의 문자 및 숫자를 분류하였으며, 하이브리드 패턴벡터 및 수직수평 패턴벡터를 사용하여 식별마크, 문자 및 숫자를 인식하여 차량 정보 인식율을 개선하였다. 제안한 알고리즘에서는 차량의 식별마크가 차량의 종류에 따라 독립적인 특성, 식별마크와 번호판 영역에서는 문자와 배경이 뚜렷하게 구별되는 특성 및 수평 및 수직빈도수 분포가 식별마크 및 번호판 이외의 영역과 뚜렷이 구별된다는 특성들을 이용하였다. 제안한 방법의 성능을 확인하기 위하여 다양한 환경에서 촬영된 350여개의 영상에 대하여 차량인식 실험을 수행하였고 제안한 방법이 차량번호판의 크기와 위치에 무관하고 잡음의 영향에 덜 민감하였을 뿐만 아니라 불규칙적인 외부환경에서도 인식율이 개선되었다. 또한 식별마크와 번호판 인식의 실시간 처리가 가능하여 실제 주차장이나 도시화도로등에 적용이 가능하다.

• Journal of Information Processing Systems
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• 제14권6호
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• pp.1445-1456
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• 2018

Environment perception and three-dimensional (3D) reconstruction tasks are used to provide unmanned ground vehicle (UGV) with driving awareness interfaces. The speed of obstacle segmentation and surrounding terrain reconstruction crucially influences decision making in UGVs. To increase the processing speed of environment information analysis, we develop a CPU-GPU hybrid system of automatic environment perception and 3D terrain reconstruction based on the integration of multiple sensors. The system consists of three functional modules, namely, multi-sensor data collection and pre-processing, environment perception, and 3D reconstruction. To integrate individual datasets collected from different sensors, the pre-processing function registers the sensed LiDAR (light detection and ranging) point clouds, video sequences, and motion information into a global terrain model after filtering redundant and noise data according to the redundancy removal principle. In the environment perception module, the registered discrete points are clustered into ground surface and individual objects by using a ground segmentation method and a connected component labeling algorithm. The estimated ground surface and non-ground objects indicate the terrain to be traversed and obstacles in the environment, thus creating driving awareness. The 3D reconstruction module calibrates the projection matrix between the mounted LiDAR and cameras to map the local point clouds onto the captured video images. Texture meshes and color particle models are used to reconstruct the ground surface and objects of the 3D terrain model, respectively. To accelerate the proposed system, we apply the GPU parallel computation method to implement the applied computer graphics and image processing algorithms in parallel.

• 한국멀티미디어학회논문지
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• 제24권12호
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• pp.1589-1597
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• 2021

Due to the low output rate and time delay of vehicle's navigation results, the electro-optical tracking system(EOTS) cannot estimate accurate target positions. If an inertial measurement unit(IMU) is additionally mounted into the EOTS and inertial navigation system(INS) is constructed, the high navigation output rate can be obtained. And the time-delay can be compensated by using the augmented Kalman filter. An accurate initial attitude is required in order to have accurate navigation outputs. In this paper, an attitude determination algorithm is proposed using the augmented Kalman filter in order to compensate measurement delay of the EOTS and have accurate initial attitude. The proposed initial attitude determination algorithm consists of an augmented Kalman filter, an INS, and an integrated Kalman filter. The augmented Kalman filter compensates the time-delay of the vehicle's navigation results and the integrated Kalman filter estimates the navigation error of the INS. In order to evaluate performance of the proposed algorithm, vehicle's navigation outputs and IMU measurements were generated using sensors' model-based measurement generator and initial attitude estimation errors of the proposed algorithm and the conventional algorithm without the augmented Kalman filter were compared for the generated measurements. The evaluation results show that the proposed algorithm has better accuracy.

• 문화기술의 융합
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• 제5권2호
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• pp.367-373
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• 2019

급격한 전기자동차의 증가에 따라 전기자동차의 배터리를 주행 목적이 아닌 다른 용도로 사용하려는 Vehicle-to-Grid (V2G) 기술 또한 산업계와 학계부터 큰 관심을 끌고 있다. V2G 기술의 도움으로 전기자동차의 배터리는 스마트 그리드 환경에서 에너지 저장장치, 전력공급원등의 여러 중요한 역할로의 사용이 가능해 진다. 본고 에서는 거주용 주택환경을 위한 기술인 Vehicle-to-Home(V2H), 상업용 건물을 위한 기술인 Vehicle-to-Building(V2B) 그리고 전체 전력망을 위한 기술인 Vehicle-to-Grid(V2G) 기술에 대해 자세히 알아보고 각 기술의 특성과 영향에 대해 검토한다. 또한 이 기술들의 경제적 영향에 대해서도 분석한다.

• 한국멀티미디어학회논문지
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• 제17권9호
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• pp.1092-1097
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• 2014

It is difficult to perform automatic formation flight of UAV (Unmanned Aerial vehicle) when GPS (Global Positionig System) is out of order or has a system error, since the relative position estimation in the flight group is impossible in that case. In this paper, we design a relative localization system for the automatic formation flight of UAV. For this purpose, we adopt digital beam forming (DBF) to estimate the angle with the central controller of the flight group and Particle Filtering scheme to compensate the estimation error of ToA (time of arrival) method. Computer simulation results present a proper distance between the central controller and a following unit to maintain the automatic formation flight.

• 한국멀티미디어학회논문지
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• 제21권11호
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• pp.1327-1332
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• 2018

An AGV(Automated Guided Vehicle) where is running on production automated system is related efficiency of production system similarly. On previous study proposed a path collision avoidance algorithms using shortest path of AGV. Running time about loading and unloading with shortest path of AGV is important factor to decide the production system efficiency. In this paper, we propose a method of shortest path and shortest time. Also propose the decision making method of collision avoidance position for setup a shortest runway for next command. To do verify the proposed method consist a simulation for AGV. Finally, we compare and analyse the proposed system between the existing system and show that our system can effectively the performance.

• 한국멀티미디어학회논문지
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• 제11권8호
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• pp.1051-1058
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• 2008

영상처리와 통신 기술의 진보는 통합된 시스템의 일부분으로써 긴급 차량 우선권과 통행 우선 방법 모두를 수용하기 위한 현행 교통 신호 제어기들과 차량 탐지 기술을 가능하게 만들고 있다. 횡단보도에서 현행 교통 신호제어는 고정된 신호 주기에 따라 변하도록 구성되어 있다. 고정된 신호 주기의 신호제어 체계는 통행량이 없는 상황에서도 일정한 신호주기가 주어지기 때문에 상대적으로 교통량이 많은 곳에서는 해당 진행 신호가 부여될 때까지 대기해야 한다. 이러한 대기 시간은 신호 위반에 따른 교통사고의 위험과 교통체증을 유발하게 된다. 본 논문에서는 교통사고의 위험과 교통 체증을 해소하기 위한 방안으로 객체 검출영상을 통하여 현장상황에 맞게 우선적으로 신호가 부여될 수 있도록 적응형 우선순위 교통신호 제어 시스템을 설계하고 시뮬레이션 하였다.

• 한국멀티미디어학회논문지
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• 제10권6호
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• pp.726-736
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• 2007

In this paper, real-time image scanning system using linescan cameras is designed. The system is specially designed to diagnose and analyse the conditions of tunnels such as crack widths through the captured images. The system consists of two major parts, the image acquisition system and the image merging system. To save scanned image data into storage media in real-time, the image acquisition system has been designed with two different control and management modules. The control modules are in charge of controlling the hardware device and the management modules handle system resources so that the scanned images are safely saved to the magnetic storage devices. The system can be mounted to various kinds of vehicles. After taking images, the image merging system generates extended images by combining saved images. Several tests are conducted in laboratory as well as in the field. In the laboratory simulation, both systems are tested several times and upgraded. In the field-testing, the image acquisition system is mounted to a specially designed vehicle and images of the interior surface of the tunnel are captured. The system is successfully tested in a real tunnel with a vehicle at the speed of 20 km/h. The captured images of the tunnel condition including cracks are vivid enough for an expert to diagnose the state of the tunnel using images instead of seeing through his/her eyes.

• IEIE Transactions on Smart Processing and Computing
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• 제4권6호
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• pp.391-402
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• 2015

In this paper, we present implementation of backward movement control of truck-trailer vehicles using a fuzzy mode-based control scheme considering practical constraints and computational overhead. We propose a fuzzy feedback controller where output is predicted with the delay of a unit sampling period. Analysis and design of the proposed controller is very easy, because it is synchronized with sampling time. Stability analysis is also possible when quantization exists in the implementation of fuzzy control architectures, and we show that if the trivial solution of the fuzzy control system without quantization is asymptotically stable, then the solutions of the fuzzy control system with quantization are uniformly ultimately bounded. Experimental results using a toy truck show that the proposed control system outperforms a conventional system.

• Journal of Multimedia Information System
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• 제4권4호
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• pp.195-204
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• 2017

Mobile robots are used for years as a valuable research and educational tool in form of available open-platform designs and Do-It-Yourself kits. Rapid development and costs reduction of Unmanned Air Vehicles (UAV) and ground based mobile robots in recent years allowed researchers to utilize them as an affordable research platform. Despite of recent developments in the area of ground and airborne robotics, only few examples of Unmanned Surface Vehicle (USV) platforms targeted for research purposes can be found. Aim of this paper is to present the development of open-design USV drone with integrated multi-level control hardware architecture. Proposed catamaran - type water surface drone enables direct control over wireless radio link, separate development of algorithms for optimal propulsion control, navigation and communication with the ground-based control station. Whole design is highly modular, where each component can be replaced or modified according to desired task, payload or environmental conditions. Developed USV is planned to be utilized as a part of the system for detection and identification of marine and lake waste. Cameras mounted to the USV would record sea or lake surfaces, and recorded video sequences and images would be processed by state-of-the-art computer vision and machine learning algorithms in order to identify and classify marine and lake waste.