• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1992년도 추계학술대회 논문집
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• pp.266-270
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• 1992

In this study an active vision system using a laser range finder is proposed for the navigation of a mobile robot in unknown environment. The laser range finder consists of a slitted laser beam generator, a scanning mechanism, CCD camera, and a signal processing unit. A laser beam from laser source is slitted by a set of cylindrical lenses and the slitted laser beam is emitted up and down and rotates around the robot by the scanning mechanism. The image of laser beam reflected on the surface of an object is engraved on the CCD array. A high speed image processing algorithm is proposed for the real-time navigation of the mobile robot. Through experiments it is proved that the accurate and real-time recognition of environment is able to be realized using the proposed laser range finder.

• 한국항해학회지
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• 제23권4호
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• pp.105-114
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• 1999

Generally, though we use the vision sensor or arc sensor in welding process, it is difficult to define the welding parameters which can be applied to the weld quality control. Especially, the important Parameters is Arc Voltage, Welding Current, Welding Speed in arc welding process and they affect the decision of weld bead shape, the stability of welding process and the decision of weld quality. Therefore, it is difficult to determine the unique relationship between the weld bead geometry and the combination of various welding condition. Due to the various difficulties as mentioned, we intend to use Fuzzy Logic and Neural Network to solve these problems. Therefore, the combination of Fuzzy Logic and Neural network has an effect on removing the weld defects, improving the weld quality and turning the desired weld bead shape. Finally, this system can be used under what kind of welding recess adequately and help us make an estimate of the weld bead shape and remove the weld defects.

• 한국항행학회논문지
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• 제14권4호
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• pp.553-561
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• 2010

본 논문에서는 로봇의 시각시스템에 효과적으로 적용할 수 있는 얼굴 추적 방법을 제안하였다. 제안한 알고리즘은 동영상의 움직임 영역을 검출한 후 얼굴 영역을 추적한다. 동영상의 움직임 검출은 연속되는 2개의 프레임을 사용하여 차영상을 구한 후, 잡음을 제거하기 위한 방법으로 메디안 필터와 침식 및 팽창연산을 사용하여 움직임 영역을 검출한다. 움직임 영역에서 피부색을 추출하기 위하여 표본영상의 칼라 정보를 이용하였다. 칼라정보의 MIN-MAX값을 퍼지화 데이터로 멤버십 함수를 생성한 후, 유사도를 평가하여 피부색 영역과 배경영역을 분리하였다. 얼굴 후보영역에 대하여 CMY 칼라 공간 C 채널에서 눈을 검출하고, YIQ 칼라 공간 Q 채널에서 입을 검출하였다. 지식기반으로 검출된 눈과 입의 특징을 찾아가며 얼굴영역을 추적하였다. 실험영상으로는 10명 각각에 대하여 150프레임의 동영상 총 1,500프레임을 입력받아 실험한 결과, 1,435프레임의 영상에 대하여 움직임 영역이 검출되어 95.7%의 프레임 검출율을 보였으며, 1,401개에 대한 얼굴을 추적 97.6%의 우수한 얼굴 추적결과를 나타내었다.

• ETRI Journal
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• 제41권4호
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• pp.506-514
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• 2019

Currently, studies on autonomous driving are being actively conducted. Vehicle positioning techniques are very important in the autonomous driving area. Currently, the global positioning system (GPS) is the most widely used technology for vehicle positioning. Although technologies such as the inertial navigation system and vision are used in combination with GPS to enhance precision, there is a limitation in measuring the lane and position in shaded areas of GPS, like tunnels. To solve such problems, this paper presents the use of LED lighting for position estimation in GPS shadow areas. This paper presents simulations in the environment of three-lane tunnels with LEDs of different color temperatures, and the results show that position estimation is possible by the analyzing chromaticity of LED lights. To improve the precision of positioning, a fuzzy logic system is added to the location function in the literature [1]. The experimental results showed that the average error was 0.0619 cm, and verify that the performance of developed position estimation system is viable compared with previous works.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2008년도 International Symposium on Remote Sensing
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• pp.137-140
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• 2008

Recently many areas require wide field of view images. Such as surveillance, virtual reality, navigation and 3D scene reconstruction. Conventional camera systems have a limited filed of view and provide partial information about the scene. however, omni directional vision system can overcome these disadvantages. Acquiring 360 degree panorama images requires expensive omni camera lens. In this study, 360 degree panorama image was tested using a low cost optical reflector which captures 360 degree panoramic views with single shot. This 360 degree panorama image system can be used with detailed positional information from GPS/INS. Through this study result, we show 360 degree panorama image is very effective tool for mobile monitoring system.

• 한국군사과학기술학회지
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• 제15권2호
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• pp.169-176
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• 2012

GPS(Global Positioning System) is widely used for the position estimation of an aerial vehicle. However, GPS may not be available due to hostile jamming or strategic reasons. A vision-based position estimation method can be effective if GPS does not work properly. In mountainous areas without any man-made landmark, a horizon is a good feature for estimating the position of an aerial vehicle. In this paper, we present a new method to estimate the position of the aerial vehicle equipped with a forward-looking infrared camera. It is assumed that INS(Inertial Navigation System) provides the attitudes of an aerial vehicle and a camera. The horizon extracted from an infrared image is compared with horizon models generated from DEM(Digital Elevation Map). Because of a narrow field of view of the camera, two images with a different camera view are utilized to estimate a position. The algorithm is tested using real infrared images acquired on the ground. The experimental results show that the method can be used for estimating the position of an aerial vehicle.

• 한국통신학회논문지
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• 제41권10호
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• pp.1247-1255
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• 2016

소형드론의 상용화를 위해서는 안전성과 자율운행기능의 확보가 필수적이다. 최근 드론제작이 상당히 용이해졌으나, 여전히 안정적인 드론의 제작은 쉽지 않다. 따라서 자체드론제작 필요성은 영상이나 자율이동 등 상위 알고리즘의 연구에 큰 장애요소로 존재한다. 본 연구에서는 상용드론과 Raspberry PI, 및 오픈소스를 활용하여, 쿼드로터 드론의 자율운행기술 개발 중 영상기반 자율운행을 설계해볼 수 있는 지상원격제어시스템(GCS)을 설계하고 구현하였다. 설계한 시스템은 모듈화된 구성으로 통신, UI 및 영상처리 모듈로 구성하였고, 특히 주행선유지 알고리즘을 구현하여 기능 및 성능 실험을 하였다. 설계한 주행선유지 알고리즘은 Hough 변환에 의하여 검출된 차선을 소실점 검출과 자제적인 라인트래킹 알고리즘을 개발하여 사용하여 인식오류를 줄였으며, 주행선과 드론의 진행방향을 계산하고 방향 (전진, 정지, 좌우회전)제어하였다. 구현된 시스템은 현재 100m육상트랙의 직선과 완만한 곡선을 2-3 m/s로 주행할 수 있다.

• 제어로봇시스템학회논문지
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• 제15권4호
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• pp.400-405
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• 2009

A new method for the catadioptric omnidirectional stereo vision with single camera is presented in this paper. The proposed method uses a concave lens with a convex mirror. Since the optical part of the proposed method is simple and commercially available, the resultant omnidirectional stereo system becomes versatile and cost-effective. The closed-form solution for 3D distance computation is presented based on the simple optics including the reflection and the reflection of the convex mirror and the concave lens. The compactness of the system and the simplicity of the image processing make the omnidirectional stereo system appropriate for real-time applications such as autonomous navigation of a mobile robot or the object manipulation. In order to verify the feasibility of the proposed method, an experimental prototype is implemented.

• 전자공학회논문지
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• 제53권1호
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• pp.118-125
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• 2016

본 논문에서는 얼굴 영역 수술용 네비게이션을 위한 스테레오 비전과 CT 영상을 이용하여 환자-영상 간 정합(Image to patient registration) 알고리즘의 성능을 평가한다. 환자 영상 간 정합은 스테레오 비전 영상의 특징점 추출과 이를 통한 3차원 좌표 계산, 3차원 좌표와 3차원 CT 영상과의 정합 과정을 거친다. 스테레오 비전 영상에서 3가지 얼굴 특징점 추출 방법과 3가지 정합 방법을 사용하여 생성될 수 있는 5가지 조합 중 정합 정확도가 가장 높은 방법을 평가한다. 또한 머리의 회전에 따라 환자 영상 간 정합의 정확도를 비교한다. 실험을 통해 머리의 회전 각도가 약 20도의 범위 내에서 Active Appearance Model과 Pseudo Inverse Matching을 사용한 정합의 정확도가 가장 높았으며, 각도가 20도 이상일 경우 Speeded Up Robust Features와 Iterative Closest Point를 사용하였을 때 정합 정확도가 높았다. 이 결과를 통해 회전각도가 20도 범위 내에서는 Active Appearance Model과 Pseudo Inverse Matching 방법을 사용하고, 20도 이상의 경우 Speeded Up Robust Features와 Iterative Closest Point를 이용하는 것이 정합의 오차를 줄일 수 있다.

• International Journal of Automotive Technology
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• 제3권2호
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• pp.71-78
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• 2002

A new control method far vision-based autonomous vehicle is proposed to determine navigation direction by analyzing lane information from a camera and to navigate a vehicle. In this paper, characteristic featured data points are extracted from lane images using a lane recognition algorithm. Then the vehicle is controlled using new Levenberg-Marquardt neural network algorithm. To verify the usefulness of the algorithm, another algorithm, which utilizes the geometric relation of a camera and vehicle, is introduced. The second one involves transformation from an image coordinate to a vehicle coordinate, then steering is determined from Ackermann angle. The steering scheme using Ackermann angle is heavily depends on the correct geometric data of a vehicle and a camera. Meanwhile, the proposed neural network algorithm does not need geometric relations and it depends on the driving style of human driver. The proposed method is superior than other referenced neural network algorithms such as conjugate gradient method or gradient decent one in autonomous lateral control .