• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.4B
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• pp.353-364
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• 2002

In this paper, a new onto-digital stereo object-tracking system using hierarchical digital algorithms and optical BPEJTC is proposed. This proposed system can adaptively track a moving target by controlling the convergence of stereo camera. firstly, the target is detected through the background matching of the sequential input images by using optical BPEJTC and then the target area is segmented by using the target projection mask which is composed by hierarchical digital processing of image subtraction, logical operation and morphological filtering. Secondly, the location's coordinate of the moving target object for each of the sequential input frames can be extracted through carrying out optical BPEJTC between the reference image of the target region mask and the stereo input image. Finally, the convergence and pan/tilt of stereo camera can be sequentially controlled by using these target coordinate values and the target can be kept in tracking. Also, a possibility of real-time implementation of the adaptive stereo object tracking system is suggested through optically implementing the proposed target extraction and convergence control algorithms.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.2
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• pp.450-460
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• 2017

T wave is cardiac parameters that represent ventricular repolarization, it is very important to diagnose arrhythmia. Several methods for detecting T wave have been proposed, such as frequency analysis and non-linear approach. However, detection accuracy is at the lower level. This is because of the overlap of the P wave and T wave depending on the heart condition. We propose T wave detection algorithm based on target area extraction through QRS cancellation and moving average. For this purpose, we detected Q, R, S wave from noise-free ECG(electrocardiogram) signal through the preprocessing method. And then we extracted P, T target area by applying decision rule for four PAC(premature atrial contraction) pattern another arrhythmia through moving average and detected T wave using RT interval and threshold of RR interval. The performance of T wave detection is evaluated by using 48 record of MIT-BIH arrhythmia database. The achieved scores indicate the average detection rate of 95.32%.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.27 no.5
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• pp.697-704
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• 2003

In this paper, the visual tracking system for arbitrary shaped moving object is proposed. The established tracking system can be divided into model based method that needs previous model for target object and image based method that uses image feature. In the model based method, the reliable tracking is possible, but simplification of the shape is necessary and the application is restricted to definite target mod el. On the other hand, in the image based method, the process speed can be increased, but the shape information is lost and the tracking system is sensitive to image noise. The proposed tracking system is composed of the extraction process that recognizes the existence of moving object and tracking process that extracts dynamic characteristics and shape information of the target objects. Specially, active contour model is used to effectively track the object that is undergoing shape change. In initializatio n process of the contour model, the semi-automatic operation can be avoided and the convergence speed of the contour can be increased by the proposed effective initialization method. Also, for the efficient solution of the correspondence problem in multiple objects tracking, the variation function that uses the variation of position structure in image frame and snake energy level is proposed. In order to verify the validity and effectiveness of the proposed tracking system, real time tracking experiment for multiple moving objects is implemented.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.32B no.11
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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.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.8
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• pp.1802-1808
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• 2003

In this paper, we propose a method about the extraction of the pedestrian tracking trajectory in the road and we used the method of mosaic background extraction and adaptive neural network for automatic pedestrian tracking system. We used mosaic background extraction to overcome ghost phenomenon. And we detected pedestrian using differential image analysis. We used adaptive neural network for multiple pedestrian tracking that non­rigid form moving. The ART2 network is capable of detecting the mass­centers of moving objects within one frame. The history of neurons positions in the sequential frames approximates the traces of the targets. The experiments done with the network in simulated environment show promising results.

• Journal of the Korea Computer Industry Society
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• v.3 no.9
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• pp.1145-1156
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• 2002

A method to measure the speed and distance of moving object is proposed using the stereo vision system. One of the most important factors for measuring the speed and distance of moving object is the accuracy of object tracking. Accordingly, the background image algorithm is adopted to track the rapidly moving object and the local opening operator algorithm is used to remove the shadow and noise of object. The extraction efficiency of moving object is improved by using the adaptive threshold algorithm independent to variation of brightness. Since the left and right central points are compensated, the more exact speed and distance of object can be measured. Using the background image algorithm and local opening operator algorithm, the computational processes are reduced and it is possible to achieve the real-time processing of the speed and distance of moving object. The simulation results show that background image algorithm can track the moving object more rapidly than any other algorithm. The application of adaptive threshold algorithm improved the extraction efficiency of the target by reducing the candidate areas. Since the central point of the target is compensated by using the binocular parallax, the error of measurement for the speed and distance of moving object is reduced. The error rate of measurement for the distance from the stereo camera to moving object and for the speed of moving object are 2.68% and 3.32%, respectively.

• International Journal of Precision Engineering and Manufacturing
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• v.5 no.1
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• pp.27-35
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• 2004

In the field of machine vision using a single camera mounted on a mobile robot, although the detection and tracking of moving objects from a moving observer, is complex and computationally demanding task. In this paper, we propose a new scheme for a mobile robot to track and capture a moving object using images of a camera. The system consists of the following modules: data acquisition, feature extraction and visual tracking, and trajectory generation. And a single camera is used as visual sensors to capture image sequences of a moving object. The moving object is assumed to be a point-object and projected onto an image plane to form a geometrical constraint equation that provides position data of the object based on the kinematics of the active camera. Uncertainties in the position estimation caused by the point-object assumption are compensated using the Kalman filter. To generate the shortest time trajectory to capture the moving object, the linear and angular velocities are estimated and utilized. The experimental results of tracking and capturing of the target object with the mobile robot are presented.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.158.5-158
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• 2001

Monopulse active homing radar requires velocity and angle information of target to track fast moving target. Target velocity can be estimated by measuring the frequency shift between transmitted and received frequencies. Angle information is obtained by measuring boresight error. Measurement of doppler frequency component in received signal is done through FFT analysis and interpolation algorithm for fine tuning. Boresight errors in azimuth and elevation axes are proportional to the power of each difference channel relative to sum channel. The target signal power in difference channel is estimated more precisely by measuring the power of FFT result cell of maximum ...

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.5
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• pp.275-280
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• 2013

In this paper, a new stereo object extraction algorithm using a block-based MSE (mean square error) algorithm and the configuration parameters of a stereo camera is proposed. That is, by applying the SSD algorithm between the initial reference image and the next stereo input image, location coordinates of a target object in the right and left images are acquired and then with these values, the pan/tilt system is controlled. And using the moving angle of this pan/tilt system and the configulation parameters of the stereo camera system, the mask window size of a target object is adaptively determined. The newly segmented target image is used as a reference image in the next stage and it is automatically updated in the course of target tracking basing on the same procedure. Meanwhile, a target object is under tracking through continuously controlling the convergence and FOV by using the sequentiall extracted location coordinates of a moving target.

• The KIPS Transactions:PartB
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• v.10B no.1
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• pp.81-86
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• 2003

In this paper, we propose the tracking method of moving object which use extracted object by difference between background image and target image in fixed domain. As a extraction method of object, calculate not pixel of full image but predefined some edge pixel of image to get a position of new object. Since the center area Is excluded from calculation, the extraction time is efficiently reduced. To extract object in the predefined area, get a starting point in advance and then extract size of width and height of object. Central coordinate is used to track moved object.