• 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.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.27 no.10
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• pp.900-908
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• 2016

In this paper, we have studied the tracking system with a single channel monopulse receiver that has a comparative advantage of costs, size, weight, and power consumption over the general 3-channel monopulse receivers. After the single channel monopulse system was composed of an antenna, a monopulse receiver, a servo unit, a RF signal processor unit and a power supply unit, we analyzed the basic tracking performance of the tracking error angle and the pointing loss. And we proved the tracking performance to a moving target in the outdoor environment. On the Analysis of the tracking test results, the single channel monopulse system shows a equal or higher performance over the general 3-channel monopulse system and also has advantages of the system implementation. Also, it is concluded that this study is useful to apply a single channel monopulse receiver with benefits of production price and miniaturization when the monopulse tracking systems will be developed in the future.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.51 no.2
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• pp.272-278
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• 2015

The aim of this study is to find out the behavior and acoustic backscattering of the large jellyfish Nemopliema nomurai using hydroacoustics in situ. N. nomurai was distributed at depths ranging from 10~15 m during the day. Regarding the behavior of N. nomurai, there was no significant change in depth, and 3D tortuosity was not high. The vertical direction was ${\pm}10^{\circ}$ from the horizontal, and moving speed was $0.9{\sim}1.5\;m\;s^{-1}$. With regard to hydro-acoustical characteristics, the mean TS of N. nomurai ranged from -69.6~-56.0 dB at 38 kHz and -69.4~-54.5 dB at 120 kHz. TS variation (Max TS-Min TS) at 38 and 120 kHz was 0~10.2 dB and 0.2~16.0 dB, respectively. Mean TS and TS variation (Max TS-Min TS) of N. nomurai were higher at 120 kHz than at 38 kHz. The results showed that the use of hydroacoustics was effective in estimating the distribution depth, behavior, and acoustic characteristics of the target.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.5A
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• pp.375-387
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• 2012

This paper proposes a new real-time object tracking algorithm using particle filters with color and texture features in moving CCD camera images. If the user selects an initial object, this region is declared as a target particle and an initial state is modeled. Then, N particles are generated based on random distribution and CS-LBP (Centre Symmetric Local Binary Patterns) for texture model and weighted color distribution is modeled from each particle. For observation likelihoods estimation, Bhattacharyya distance between particles and their feature models are calculated and this observation likelihoods are used for weights of individual particles. After weights estimation, a new particle which has the maximum weight is selected and new particles are re-sampled using the maximum particle. For performance comparison, we tested a few combinations of features and particle filters. The proposed algorithm showed best object tracking performance when we used color and texture model simultaneously for likelihood estimation.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.9
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• pp.238-247
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• 2014

The milking robot system is very important to detect correctly the teats position in the moving condition of cow. Also, the robot manipulator must control tracking the teat cup to the detected teat position. The presented milking robot is designed using the one point laser sensor for teat position detection. The teats of cow are detected by the laser scanning unit and the manipulator has the function of 3 axes moving control unit. The presented teat detection method and the electrical driving manipulator have the advantages of a simple, low cost and very quiet. The designed manipulator is realized by the totally electrical motor and servo poison control algorithm with velocity PID compensation. The presented robot is realized using the teat detection unit, 4 teat cups, 3 axes robot arm, 6 servo motors and automatic milking control line. The designed robot is experimented in the cow farm and is satisfied with the designed performance specification for milking robot manipulator.

• Journal of KIISE:Software and Applications
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• v.31 no.11
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• pp.1496-1504
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• 2004

In this paper, we propose an algorithm for initializing a target vehicle detection, tracking the vehicle and estimating the distance from it on the stereo images acquired from a forward-looking stereo camera mounted on a road driving vehicle. The process of vehicle detection extracts road region using lane recognition and searches vehicle feature from road region. The distance of tracking vehicle is estimated by TSS correlogram matching from stereo Images. Through the simulation, this paper shows that the proposed method segments, matches and tracks vehicles robustly from image sequences obtained by moving stereo camera.

• The Journal of Korea Robotics Society
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• v.15 no.3
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• pp.221-232
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• 2020

In a four-wheel independent drive platform, four wheels and motors are connected directly, and the rotation of the motors generates the power of the platform. It uses a skid steering system that steers based on the difference in rotational power between wheel motors. The platform can control the speed of each wheel individually and has excellent mobility on dirt roads. However, the difficulty of the straight-running is caused due to torque distribution variation in each wheel's motor, and the direction of rotation of the wheel, and moving direction of the platform, and the difference of the platform's target direction. This paper describes an algorithm to detect the slip generated on each wheel when a four-wheel independent drive platform is traveling in a harsh environment. When the slip is detected, a compensation control algorithm is activated to compensate the torque of the motor mounted on the platform to improve the trajectory tracking performance of the platform. The four-wheel independent drive platform developed for this study verified the algorithm. The wheel slip detection and the compensation control algorithm of the platform are expected to improve the stability of trajectory tracking.

• 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.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.38 no.2
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• pp.160-168
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• 2001

Change detection using difference picture has been used to detect the location of moving targets and to track them. This method needs the assumption of static camera, and the global motion compensation is required in case of a moving camera. This paper suggests a method for finding a minimum bounding rectangles(MBR) of moving targets in the image sequences using moving region detection, especially with a moving camera. If the global motion parameter is inaccurately estimated, the estimated locations of targets will be accurate either To alleviate this problem, we introduce the concept of the confidence measure and achieve more accurate estimation of global motion. Experimental results show that the proposed method successfully removes background region and extracts MBRs of the targets. Even with a moving camera, the new global motion estimation algorithm performs more precise]y and it reduces the background compensation errors of change detection.

• Journal of Broadcast Engineering
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• v.23 no.3
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• pp.409-420
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• 2018

In this paper, we propose a Motion Vector-based Particle Filter(MVPF) for object tracking on bitstreams and a object tracking system using the MVPF. The MVPF uses motion vectors to both the transition and the observation models of a general particle filter to improve the accuracy while maintaining the number of particles. In the proposed object tracking system, the state of the target object can be predicted using the histogram of motion vectors extracted from the bitstream. In terms of precision, F-measure and IOU(Intersection Of Union), the proposed method is about 30%, 17%, and 17% better on average, respectively, in MPEG test sequences and VOT2013 sequences. Furthermore, When the tracking results are displayed in box form for subjective performance evaluation, the proposed method can track moving objects more robust than the conventional methods in all test sequences.