• 한국인터넷방송통신학회논문지
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• 제8권3호
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• pp.35-45
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• 2008

카메라를 이용한 실시간 시정측정은 인간의 시정 감각과 유사하고 현실성 있는 시정자료를 획득할 수 있으며 기존 고가의 광학기기를 이용한 측정방법을 대체할 수 있는 새로운 측정방식이다. 영상으로부터 깊이정보나 3차원 구조의 추출 등을 통해 시정을 측정하려는 시도가 있으나, 단순하고 빠른 처리가 요구되는 실시간 시정측정과 이동물체가 많이 나타나는 경우에는 많은 문제점을 갖고 있다. 본 논문에서는 시정의 감소는 영상에서 지수적인 대비의 감소로 나타난다는 점에 착안하여 영상으로부터 이동영역 필터를 이용하여 대비를 추출하고 영상대비와 시정간의 상관관계를 수학적으로 모델링함으로써 쉽고 빠르게 시정을 측정할 수 있는 방법을 제안한다. 이동영역 필터는 영상으로부터 시정측정에 영향을 주는 하늘과 물체의 이동영역을 효과적으로 제거하기 위해 사용된다. 제안된 방법은 카메라를 통해 입력된 영상으로부터 실시간 시정측정이 가능할 뿐만 아니라 도로와 같이 차량의 이동이 많은 경우에도 안정적인 시정측정이 가능하다.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1996년도 춘계학술대회 논문집
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• pp.254-258
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• 1996

In this paper, we proposed realtime visual tracking system of moving object for 2D target using extended Kalman Filter Algorithm. A targeting marker are recongnized in each image frame and positions of targer object in each frame from a CCD camera while te targeting marker is attached to the tip of the SCARA robot hand. After the detection of a target coming into any position of the field-of-view, the target is tracked and always made to be located at the center of target window. Then, we can track the moving object which moved in inter-frames. The experimental results show the effectiveness of the Kalman filter algorithm for realtime tracking and estimated state value of filter, predicting the position of moving object to minimize an image processing area, and by reducing the effect by quantization noise of image

• 한국정밀공학회지
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• 제15권7호
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• pp.175-181
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• 1998

This paper describes realtime visual tracking system of moving object for three dimensional target using EKF(Extended Kalman Filter). We present a new realtime visual tracking using EKF algorithm and image prediction algorithm. We demonstrate the performance of these tracking algorithm through real experiment. The experimental results show the effectiveness of the EKF algorithm and image prediction algorithm for realtime tracking and estimated state value of filter, predicting the position of moving object to minimize an image processing area, and by reducing the effect by quantization noise of image.

• 전기학회논문지
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• 제65권3호
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• pp.477-486
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• 2016

This paper presents the area classification, identification, and tracking for multiple moving objects with the similar colors. To do this, first, we use the GMM(Gaussian Mixture Model)-based background modeling method to detect the moving objects. Second, we propose the use of the binary and morphology of image in order to eliminate the shadow and noise in case of detection of the moving object. Third, we recognize ROI(region of interest) of the moving object through labeling method. And, we propose the area classification method to remove the background from the detected moving objects and the novel method for identifying the classified moving area. Also, we propose the method for tracking the identified moving object using Kalman filter. To the end, we propose the effective tracking method when detecting the multiple objects with the similar colors. Finally, we demonstrate the feasibility and applicability of the proposed algorithms through some experiments.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권11호
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• pp.5624-5638
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• 2016

A novel method based on Surf points is proposed to detect and lock-track single ground target in aerial videos. Videos captured by moving cameras contain complex motions, which bring difficulty in moving object detection. Our approach contains three parts: moving target template detection, search area estimation and target tracking. Global motion estimation and compensation are first made by grids-sampling Surf points selecting and matching. And then, the single ground target is detected by joint spatial-temporal information processing. The temporal process is made by calculating difference between compensated reference and current image and the spatial process is implementing morphological operations and adaptive binarization. The second part improves KALMAN filter with surf points scale information to predict target position and search area adaptively. Lastly, the local Surf points of target template are matched in this search region to realize target tracking. The long-term tracking is updated following target scaling, occlusion and large deformation. Experimental results show that the algorithm can correctly detect small moving target in dynamic scenes with complex motions. It is robust to vehicle dithering and target scale changing, rotation, especially partial occlusion or temporal complete occlusion. Comparing with traditional algorithms, our method enables real time operation, processing $520{\times}390$ frames at around 15fps.

• 풍력에너지저널
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• 제10권3호
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• pp.5-11
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• 2019

This paper suggests and compares two algorithms, a moving average filter method and a method developed by the National Renewable Energy Laboratory (NREL), to verify the yaw control algorithm characteristic to reduce yaw error for a wind turbine. A characteristic change for yaw movement in accordance with control parameter change that consists of each control method has been verified. Also, yaw simulations were performed using nacelle wind data measured from two areas with different turbulence intensities and the yaw movement data in each area was compared. These two algorithms and real data were compared by calculating mean absolute error (MSE) and the number of yawing (NY). As a result of the analysis, the MSE values were not significantly different between the two algorithms, but the algorithm proposed by the NREL was found to reduce yaw movement by up to 50 percent more than the moving average filter method.

• 제어로봇시스템학회논문지
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• 제21권7호
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• pp.641-647
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• 2015

This paper proposes a new strategy for a quad-rotor to track a moving object efficiently by using image processing and an extended Kalman filter. The goal of path planning for the quad-rotor is to design an optimal path from the start point to the destination point. To lengthen the freight time of the quad-rotor, an optimal path is required to reduce the energy consumption. To track a moving object, the mark signed on the moving object has been detected by a camera mounted first on the quad-rotor. The center coordinates of the mark and its area are calculated through the blob analysis which is one type of image processing. The mark coordinates are utilized to obtain information on the motion direction and the area of the mark is utilized to recognize whether the object moves backward or forward from the camera on the quad-rotor. In addition, an extended Kalman filter has been applied to predict the direction and speed of the dynamically moving object. Through these schemes, it is aimed that the quad-rotor can track the dynamic object efficiently in terms of flight distance and time. Through the two different route freights of the quad-rotor, the performance of the proposed system has been demonstrated.

• Journal of information and communication convergence engineering
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• 제9권6호
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• pp.747-752
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• 2011

The position detection of overlapping area in the interframe for image stitching using auto and cross correlation function (ACCF) and compounding one image with the stitching algorithm is presented in this paper. ACCF is used by autocorrelation to the featured area to extract the filter mask in the reference (previous) image and the comparing (current) image is used by crosscorrelation. The stitching is detected by the position of high correlation, and aligns and stitches the image in shifting the current image based on the moving vector. The ACCF technique results in a few computations and simplicity because the filter mask is given by the featuring block, and the position is enabled to detect a bit movement. Input image captured from CMOS is used to be compared with the performance between the ACCF and the window correlation. The results of ACCF show that there is no seam and distortion at the joint parts in the stitched image, and the detection performance of the moving vector is improved to 12% in comparison with the window correlation method.

• 대한전자공학회논문지SP
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• 제39권4호
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• pp.361-369
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• 2002

제한된 구역내의 고정(static)된 감시 카메라를 통해 입력된 영상 데이터에 대해 움직임이 있는 물체를 검출하기 위해서는 주위 잡음(noise)에 대한 민감성(sensitivity)과 상황변화에 대해 대처할 수 있는 강인한 알고리즘이 요구된다. 본 논문에서는 이러한 잡음이나 갑작스런 상황의 변화에 적절히 대응하여 움직임 물체를 추출하고 추적하는 효율적인 알고리즘을 제안한다. 초기 배경 모델(background model) 영상에 의해서 입력되는 영상 내에 이동 물체가 존재할 경우 각 화소의 주변의 변화를 고려하여 움직임 영역을 검출하였다. 움직임 영역의 화소들의 잡음 제거를 위해 형태학적 필터(morphological filter)를 사용하였고, 8-연결 성분 표시(connected component labeling)에 의해 개별적인 물체의 움직임을 검출하였다. 마지막으로 다양한 환경과 모델에 따른 실험결과와 통계적인 분석을 제시하였다.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2008년도 춘계종합학술대회 A
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• pp.425-428
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• 2008

본 논문에서는 위성 항법 시스템(GPS)의 불연속성과 수신 음영 지역에서의 속도 추적 한계를 극복하기 위하여 가속도계와 GPS를 이용한 이동 물체의 속도를 추정하는 시스템을 제안한다. 시스템은 이동 물체에 부착된 GPS 수신기와 가속도계의 항법 정보를 입력받아 물체의 진동과 충격 그리고 가속도계 자체의 오차에 기인한 잡음을 보정하고, 이를 이용하여 GPS 음영 지역에서 이동 물체의 속도 추정과 GPS 항법 정보의 불연속성을 보완할 수 있도록 설계되었다. 본 시스템에 사용하기 위해 GPS와 가속도계를 이용한 칼만 필터 구조를 설계하고, GPS 수신 음영 지역에서도 물체의 속도를 추적할 수 있음을 검증하여, 향후 자동항법장치 등 텔레매틱스 산업에서의 응용 가능성을 제시하고자 한다.