• 대한임베디드공학회논문지
• /
• 제6권1호
• /
• pp.8-15
• /
• 2011

This paper presents an effective method for detecting vehicles in front of the camera-assisted car during nighttime driving. The proposed method detects vehicles based on detecting vehicle headlights and taillights using techniques of image segmentation and clustering. First, in order to effectively extract spotlight of interest, a pre-signal-processing process based on camera lens filter and labeling method is applied on road-scene images. Second, to spatial clustering vehicle of detecting lamps, a grouping process use light tracking method and locating vehicle lighting patterns. For simulation, we are implemented through Da-vinci 7437 DSP board with visible light mono-camera and tested it in urban and rural roads. Through the test, classification performances are above 89% of precision rate and 94% of recall rate evaluated on real-time environment.

• 대한전기학회논문지:시스템및제어부문D
• /
• 제52권11호
• /
• pp.626-633
• /
• 2003

Theoretical analysis of the depth measurement system with the use of a single camera and a rotating mirror has been done. A camera in front of a rotating mirror acquires a sequence of reflected images, from which depth information is extracted. For an object point at a longer distance, the corresponding pixel in the sequence of images moves at a higher speed. Depth measurement based on such pixel movement is investigated. Since the mirror rotates along an axis that is in parallel with the vertical axis of the image plane, the image of an object will only move horizontally. This eases the task of finding corresponding image points. In this paper, the principle of the depth measurement-based on the relation of the pixel movement speed and the depth of objects have been investigated. Also, necessary mathematics to implement the technique is derived and presented. The factors affecting the measurement precision have been studied. Analysis shows that the measurement error increases with the increase of depth. The rotational angle of the mirror between two image-takings also affects the measurement precision. Experimental results using the real camera-mirror setup are reported.

• 대한전기학회:학술대회논문집
• /
• 대한전기학회 1999년도 하계학술대회 논문집 G
• /
• pp.3048-3050
• /
• 1999

This paper suggests a position estimating algorithm using mono vision system with projective geometry method. Generally, 3-D information can not be easily extracted from mono vision system which is taken by a camera at a specific point. But this defect is overcome by adopting model-based image analysis and selecting lines and points on the ground as natural landmarks. And this paper suggests a method that estimates position from many natural landmarks by distance error weight function.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 2005년도 ICCAS
• /
• pp.1994-1998
• /
• 2005

Characteristic analysis of the depth measurement system with a laser, a camera and a rotating mirror has been done and the parameter calibration technique for it has been proposed. In the proposed depth measurement system, the laser beam is reflected to the object by the rotating mirror and again the position of the laser beam is observed through the same mirror by the camera. The depth of the object pointed by the laser beam is computed depending on the pixel position on the CCD. There involved several number of internal and external parameters such as inter-pixel distance, focal length, position and orientation of the system components in the depth measurement error. In this paper, it is shown through the error sensitivity analysis of the parameters that the most important parameters in the sense of error sources are the angle of the laser beam and the inter pixel distance. The calibration techniques to minimize the effect of such major parameters are proposed.

• 한국정밀공학회:학술대회논문집
• /
• 한국정밀공학회 2009년도 춘계학술대회 논문집
• /
• pp.399-400
• /
• 2009

• 제어로봇시스템학회논문지
• /
• 제21권12호
• /
• pp.1089-1099
• /
• 2015

This paper proposes vision-based collision risk estimation method for an unmanned surface vehicle. A robust image-processing algorithm is suggested to detect target obstacles from the vision sensor. Vision-based Target Motion Analysis (TMA) was performed to transform visual information to target motion information. In vision-based TMA, a camera model and optical flow are adopted. Collision risk was calculated by using a fuzzy estimator that uses target motion information and vision information as input variables. To validate the suggested collision risk estimation method, an unmanned surface vehicle experiment was performed.

• 한국정밀공학회:학술대회논문집
• /
• 한국정밀공학회 2001년도 춘계학술대회 논문집
• /
• pp.590-593
• /
• 2001

In this paper we describe the 6-axes robot's position determination using a stereo vision and an image based control method. When use a stereo vision, it need a additional time to compare with mono vision system. So to reduce the time required, we use the stereo vision not image Jacobian matrix estimation but depth estimation. Image based control is not needed the high-precision of camera calibration by using a image Jacobian. The experiment is executed as devide by two part. The first is depth estimation by stereo vision and the second is robot manipulator's positioning.

• 한국전기전자재료학회:학술대회논문집
• /
• 한국전기전자재료학회 2006년도 영호남 합동 학술대회 및 춘계학술대회 논문집 센서 박막 기술교육
• /
• pp.125-129
• /
• 2006

The analysis of the depth measurement system with multi-sensors (laser, camera, mirror) has been done and the parameter calibration technique has been proposed. In the proposed depth measurement system, the laser beam is reflected to the object by the rotating mirror and again the position of the laser beam is observed through the same mirror by the camera. The depth of the object pointed by the laser beam is computed depending on the pixel position on the CCD. There involved several number of internal and external parameters such as inter-pixel distance, focal length, position and orientation of the system components in the depth measurement error. In this paper, it is shown through the error sensitivity analysis of the parameters that the most important parameters in the sense of error sources are the angle of the laser beam and the inter pixel distance.

• 한국컴퓨터정보학회논문지
• /
• 제12권6호
• /
• pp.69-76
• /
• 2007

강의 및 회의에서 발표자가 파일을 열거나 PC상의 모니터를 직접 조작하기 위하여 진행중인 발표를 멈추고 PC에 다가가 필요한 조작을 하게 되면 발표의 흐름이 끊기게 된다. 이러한 불편함을 개선하기 위한 여러 방법들이 제안되었으나 주로 레이저 빔 포인터[LBP]에 마우스 기능을 부착하여 처리하려는 시도들이 대부분이고 근본적인 해결은 되지 않고 있다. 본 논문에서는 한 개의 카메라와 영상처리 알고리즘을 적용하여 설치가 간단하고 저 가격으로도 실현이 가능하면서도 빔의 검지 위치 정도를 높인 마우스 기능이 부착된 LBP를 제안하고 구현하였으며, 실험을 통하여 마우스의 위치 인식 오차를 분석하였다. 본 연구의 결과 제안된 LBP가 카메라를 사용하였음에도 불구하고 조명의 변화나 시야각의 변화에 대해서도 검지된 빔의 위치인식의 반복성과 마우스의 커서로 사용하기에 충분한 고정도의 위치 인식 오차를 보여주고 있음을 확인하였다.

• 융합신호처리학회논문지
• /
• 제4권1호
• /
• pp.56-63
• /
• 2003

본 논문은 실제 무인주행자동차에 적용할 수 있는 비전 기반의 소형 자율이동로봇 개발에 관한 연구를 제시한다. 이전의 자율주행차량은 하드웨어 설계의 복잡성, 실장의 어려움과 많은 계산량으로 인해 PC에 대한 의존도가 높았다. 본 논문에서는 고속에서 정확한 조향 및 빠른 이동을 할 수 있고, 단일 카메라를 사용한 독립형 시스템으로 지능적 인식을 할 수 있는 소형 자율이동로봇을 제안한다. 제안된 시스템은 폭 25~30cm, 총길이 200cm로 만들어진 트랙에서 실험하였다. 실험 로봇은 직선 트랙에서 평균 32.9km/h, 곡률반경 30~40m인 곡선트랙에서 평균 22.3km/h의 속도로 주행할 수 있었다 이 시스템은 실제 무인 자동차를 쉽게 만들기 위해 사용할 수 있는 차선 인식 알고리즘을 적용한 소형 자율이동로봇 시스템에 대한 하나의 모델을 제시할 수 있었다.