• Ocean Science Journal
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• 제40권4호
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• pp.213-220
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• 2005

In this paper, image processing technique that reduces video images of buoy motion to yield time series of image coordinates of buoy objects will be investigated. The buoy motion images are noisy due to time-varying brightness as well as non-uniform background illumination. The occurrence of boats, wakes, and wind-induced white caps interferes significantly in recognition of buoy objects. Thus, semi-automated procedures consisting of object recognition and image measurement aspects will be conducted. These offer more satisfactory results than a manual process. Spectral analysis shows that the image coordinates of buoy objects represent wave motion well, indicating its usefulness in the analysis of wave characteristics.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1991년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 22-24 Oct. 1991
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• pp.990-995
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• 1991

The integration of intelligent robots into manufacturing systems should positively impact the product quality and productivity. A new theory of object location and recognition using the supporting plane is presented. The unknown supporting points are determined by image coordinates, known camera parameters, and joint coordinates of the robot manipulators. This is developed by using the geometrical interpretation of perspective projection and the geometrical constraints of industrial environments. This can be applied to solve typical robot vision problems such as determination of position, orientation, and recognition of objects.

• 한국측량학회지
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• 제4권1호
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• pp.25-36
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• 1986

지상사진으로 3차원 대상물에 대한 모든면의 절대좌표를 구하기 위해서는 최소 세쌍 이상의 모델이 필요하게 된다. 본 연구에서는 거울을 영상매개체로 이용하여 한쌍의 입체모델을 촬영하므로서 대상물의 모든면에 대한 3차원 좌표를 분석할 수 있는 기법을 연구하였으며, 거울면의 왜곡을 보정하기 위한 오차보정함수를 도입하여 거울영상기법의 정확성과 효용성을 증진시키는데 목적이 있다. 거울평면 방정식을 이용하여 거울에 투영된 점을 실제대상물상의 동일점으로 변환한 결과 X좌표의 오차가 가장크게 나타났으며, Y, Z좌표에서는 1mm 정도의 절대좌표오차를 나타내었고, 좌우거울의 보정함수를 도입하여 거울에 의한 왜곡을 보정하므로서 근거리 사진측량의 기대정확도에 만족됨을 알 수 있었다.

• 제어로봇시스템학회논문지
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• 제15권11호
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• pp.1080-1087
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• 2009

This paper presents an algorithm to acquire 3D geometric information using a virtual plane method. The method to measure 3D information on the plane is easy, because it's not concerning value on the z-axis. A plane can be made by arbitrary three points in the 3D space, so the algorithm is able to make a number of virtual planes from feature points on the target object. In this case, these geometric relations between the origin of each virtual plane and the origin of the target object coordinates should be expressed as known homogeneous matrices. To include this idea, the algorithm could induce simple matrix formula which is only concerning unknown geometric relation between the origin of target object and the origin of camera coordinates. Therefore, it's more fast and simple than other methods. For achieving the proposed method, a regular pin-hole camera model and a perspective projection matrix which is defined by a geometric relation between each coordinate system is used. In the final part of this paper, we demonstrate the techniques for a variety of applications, including measurements in industrial parts and known patches images.

• 제어로봇시스템학회논문지
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• 제11권5호
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• pp.398-405
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• 2005

The intelligent robots that will be needed in the near future are human-friendly robots that are able to coexist with humans and support humans effectively. To realize this, robots need to recognize their position and posture in known environment as well as unknown environment. Moreover, it is necessary for their localization to occur naturally. It is desirable for a robot to estimate of his position by solving uncertainty for mobile robot navigation, as one of the best important problems. In this paper, we describe a method for the localization of a mobile robot using image information of a moving object. This method combines the observed position from dead-reckoning sensors and the estimated position from the images captured by a fixed camera to localize a mobile robot. Using a priori known path of a moving object in the world coordinates and a perspective camera model, we derive the geometric constraint equations which represent the relation between image frame coordinates for a moving object and the estimated robot's position. Also, the control method is proposed to estimate position and direction between the walking human and the mobile robot, and the Kalman filter scheme is used for the estimation of the mobile robot localization. And its performance is verified by the computer simulation and the experiment.

• 전자공학회논문지B
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• 제32B권11호
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• pp.1393-1404
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• 1995

For the factory automation(FA) of production or assembly lines, computer vision techniques have been widely used for the recognition and position-control of objects. In this application, it is very important to analyze characteristic features of each object and to find an efficient matching algorithm using the selected features. If the object has regular or homogeneous patterns, the problem is relatively simple. However, If the object is shifted or rotated, and if the depth of the input visual system is not fixed, the problem becomes very complicated. Also, in order to understand and recognize objects with concentric noise patterns, it is more effective to use feature-information represented in polar coordinates than in cartesian coordinates. In this paper, an algorithm for the recognition of objects with concentric circular noise-patterns is proposed. And position-conrtol information is calculated with the matching result. First, a filtering algorithm for eliminating concentric noise patterns is proposed to obtain concentric-feature patterns. Then a shift, rotation and scale invariant alogrithm is proposed for the recognition and position-control of objects uusing invariant feature information. Experimental results indicate the effectiveness of the proposed alogrithm.

• 제어로봇시스템학회논문지
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• 제22권1호
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• pp.24-30
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• 2016

The accuracy of small and low-cost CCD cameras is insufficient to provide data for precisely tracking unmanned aerial vehicles (UAVs). This study shows how a quad rotor UAV can hover on a human targeted tracking object by using data from a CCD camera rather than imprecise GPS data. To realize this, quadcopter UAVs need to recognize their position and posture in known environments as well as unknown environments. Moreover, it is necessary for their localization to occur naturally. It is desirable for UAVs to estimate their position by solving uncertainty for quadcopter UAV hovering, as this is one of the most important problems. In this paper, we describe a method for determining the altitude of a quadcopter UAV using image information of a moving object like a walking human. This method combines the observed position from GPS sensors and the estimated position from images captured by a fixed camera to localize a UAV. Using the a priori known path of a quadcopter UAV in the world coordinates and a perspective camera model, we derive the geometric constraint equations that represent the relation between image frame coordinates for a moving object and the estimated quadcopter UAV's altitude. Since the equations are based on the geometric constraint equation, measurement error may exist all the time. The proposed method utilizes the error between the observed and estimated image coordinates to localize the quadcopter UAV. The Kalman filter scheme is applied for this method. Its performance is verified by a computer simulation and experiments.

• Spatial Information Research
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• 제13권2호
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• pp.129-138
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• 2005

본 논문에서는 스테레오 CCD 카메라를 이용하여 이동체의 3차원 위치좌표를 추출하는 알고리즘을 제안하였다. 이 알고리즘을 통해 효율적으로 이동체의 3차원 위치좌표를 추출하는 방법을 도출하고자 하였다 스테레오 CCD 카메라의 상호표정을 수행하고, 획득된 영상에서 이동체를 배경과 분리한 뒤, 좌$\cdot$우 영상에서 이동체의 영상좌표를 추출한다. 추출된 좌$\cdot$우 영상에서의 영상좌표를 이용하여 이동체의 3차원 위치를 결정하게 된다. 스테레오 CCD 카메라간의 상호 위치 및 자세를 결정하기 위한 표정 모듈은 독립적 상호표정(independent relative orientation)을 사용하였고, 획득된 영상에서 이동체 추출 알고리즘은 칼라영상의 RGB(Red, Green, Blue) 화소값을 이용하여 구현하였다. 좌$\cdot$우 CCD 카메라로부터 들어오는 영상좌표를 이용하여 공간전방교회 법을 통해 이동체의 위치를 계산하였다. 그리고 전체 시스템의 실험을 수행하였고, 그 결과의 정확도를 비교하였다.

• 한국멀티미디어학회논문지
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• 제20권7호
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• pp.1004-1013
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• 2017

This paper presents a relationship between the number of curves and geometric parameters of a 3D object. Once the relationship is established, the number of closed curves that can reliably represent 3D object is derived. Inspired by Shannon-Nyquist Sampling Theorem, in this paper, approach for sampling rate (defined as the minimum number of curves) for 3D reconstruction is proposed. The relationship is straightforward, is suitable for application to 3D object overlaid with closed-continuous curves, and can achieve efficient 3D reconstruction system in practice. To substantiate the proposed approach, simulation results are provided and the results show that the number of curves can be decreased without loss of generality of characteristics of a target 3D object.

• 전자공학회논문지B
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• 제32B권11호
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• pp.1405-1416
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• 1995

An effective algorithm for implementation of unmanned surveillance system which detects moving object from image sequences, predicts the direction of it, and drives the camera in real time is proposed. Outputs of proposed algorithm are coordinates of location of moving object, and they are converted to the values according to camera model. As a pre- processing, extraction of moving object and shape discrimination are performed. Existence of the moving object or scene change is detected by computing the temporal derivatives of consecutive two or more images in a sequence, and this result of derivatives is combined with the edge map from one original gray level image to obtain the position of moving object. Shape discri-mination(Target identification) is performed by analysis of distribution of projection profiles in x and y directions. To reduce the prediction error due to the fact that the motion cha- racteristic of walking man may have an abrupt change of moving direction, an order adaptive lattice structured linear predictor is proposed.