• Proceedings of the IEEK Conference
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• 1998.06a
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• pp.749-752
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• 1998

Recognizing a human part becomes very important for applications which are based on the interaction between computers and their users. In this paper, we design and implement a system which recognizes and tracks a human head using a sequence of images. Difference images are used to easily extract feature vectors from images with very complex backgrounds. A human bhead is represented with an ellipse and recognized by searching for a maximum value from preprocessed gradient images. The method is developed by considering the fact that the tracking system should be real-time. The designed system not only shows an excellent performance for the normal up-right position of the head, but also for the cases of 360.deg. rotated head position, occluded images of heads, and tilted head positions.

• Proceedings of the KIEE Conference
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• 2001.11c
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• pp.365-368
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• 2001

This work describes a real-time method, based on motion energy detection, for detecting and tracking moving object in the consecutive image sequences. The motion of moving objects is detected by taking the difference of the two consecutive image frames. In addition an edge information of the current image is utilized in order to further increase the accuracy of detection. We can track the moving objects continuously by detecting the motion of objects from the sequence of image frames. A prototype system has been implemented using a TI TMS320C6201 EVM fixed-point DSP board, which can successfully track a moving human in real-time.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.1
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• pp.52-58
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• 2015

In this paper, The ET-MBEF algorithm is presented for CCD imaging seeker. At the imaging seeker, target size information is important factor for accurate tracking. The MBEF algorithm was proposed to estimate target size at IIR seeker. However, the MBEF algorithm can't be applied at CCD imaginary target size estimation. In order to overcome the problem, we propose ET-MBEF algorithm which based on ET (Edge Template) and MBEF algorithm. The performance of proposed method is tested at target intercept scenario. The experiment results show that the proposed algorithm has the accurate target intercept performance.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.7
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• pp.1331-1338
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• 2011

This paper proposes a method for frequency control of islanded microgrid with battery energy storage system. For frequency control of islanded microgrid, battery energy storage system uses a phase locked loop algorithm with positive sequence components for a fast frequency estimation. Microgrid is a power system with small inertia because it has small capacity generators and inverter systems for renewable energy. So, Islanded microgrid's frequency varies fast and large as small generation and load changes. To reduce frequency variation of islanded microgrid, it needs a device with fast frequency response. For fast frequency response, a fast frequency tracking is important. To show the validation of proposed fast frequency tracking algorithm, battery energy storage system with proposed algorithm is tested in microgrid pilot plant.

• Journal of IKEEE
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• v.13 no.2
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• pp.232-240
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• 2009

This paper presents a robust vehicle detection and tracking algorithm for supervision of illegal parking. The proposed algorithm is composed of four parts. First, a vehicle detection algorithm is proposed using the improved codebook object detection algorithm to segment moving vehicles from the input sequence. Second, a preprocessing technique using the geometric characteristics of vehicles is employed to exclude non-vehicle objects. Then, the detected vehicles are tracked by an object tracker which incorporates histogram tracking method with Kalman filter. To make the tracking results more accurate, histogram tracking results are used as measurement data for Kalman filter. Finally, Real Stop Counter (RSC) is introduced for trustworthy and accurate performance of the stopped vehicle detection. Experimental results show that the proposed algorithm can track multiple vehicles simultaneously and detect stopped vehicles successfully in the complicated street environment.

• Proceedings of the Korea Contents Association Conference
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• 2003.11a
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• pp.281-284
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• 2003

In this study, we have proposed the method of moving area detection as the preprocessing step of moving object tracking system. First, we catch the two frames which are different at time in image sequence. We obtain the moving area by using their binary differential image. In differential image, the object area of previous and current frame is present. In the tracking system, the background is changed by camera motion. So, in this case we have to decide which moving area of object is current at time. We obtain the binary edge image of current frame by applying a threshold to the output of an edge detector. Then we performed logical AND operation between the edge image and differential image. As a result of this work moving area of object can be detected.

• The KIPS Transactions:PartB
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• v.12B no.7 s.103
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• pp.767-774
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• 2005

In this paper, we present a snake-based scheme for tracking object contour using disparity information taken from a stereo image sequence with cluttered background. The proposed method is composed of two steps. First, 3-D motion of object is estimated and candidate snake points are selected in disparity space. Second, object contour is extracted by using a modified snake algorithm with disparity information. The proposed algorithm can successfully extract the concave contour of objects and track the object contour in complex image. Performance of the proposed algorithm has been verified by simulation.

• Journal of Intelligence and Information Systems
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• v.8 no.2
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• pp.1-13
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• 2002

In this paper, we propose an object tracking system which can be convinced of moving area shaped on objects through color sequential images, decided moving directions of foot messengers or vehicles of image sequences. In static camera, we suggests a new evaluating method extracting co-occurrence matrix with feature vectors of RGB after analyzing and blocking difference images, which is accessed to field of camera view for motion. They are energy, entropy, contrast, maximum probability, inverse difference moment, and correlation of RGB color vectors. we describe how to analyze and compute corresponding relations of objects between adjacent frames. In the clustering, we apply an algorithm of FCM(fuzzy c means) to analyze matching and clustering problems of adjacent frames of the featured vectors, energy and entropy, gotten from previous phase. In the matching phase, we also propose a method to know correspondence relation that can track motion each objects by clustering with similar area, compute object centers and cluster around them in case of same objects based on membership function of motion area of adjacent frames.

• KIPS Transactions on Software and Data Engineering
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• v.3 no.6
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• pp.231-236
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• 2014

The transit time of contrast agents and the parameters of time-intensity curves in ultrasonography are important factors to diagnose various diseases of a digestive organ. We have implemented an automatic parametric imaging method to overcome the difficulty of the diagnosis by naked eyes. However, the micro-bubble noise and the respiratory motions may degrade the reliability of the parameter images. In this paper, we introduce an optimization technique based on MRF(Markov Random Field) model to enhance the quality of the parameter images, and present an image tracking algorithm to compensate the image distortion by respiratory motions. A method to extract the respiration periods from the ultrasound image sequence has been developed. We have implemented the ROI(Region of Interest) tracking algorithm using the dynamic weights and a momentum factor based on these periods. An energy function is defined for the Gibbs sampler of the image enhancement method. Through the experiments using the data to diagnose liver lesions, we have shown that the proposed method improves the quality of the parametric images.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.7
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• pp.2579-2585
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• 2010

This paper proposes a dynamic human pose tracking method using motion-based search strategy from an image sequence obtained from a monocular camera. The proposed method compares the image features between 3D human model projections and real input images. The method repeats the process until predefined criteria and then estimates 3D human pose that generates the best match. When searching for the best matching configuration with respect to the input image, the search region is determined from the estimated 2D image motion and then search is performed randomly for the body configuration conducted within that search region. As the 2D image motion is highly constrained, this significantly reduces the dimensionality of the feasible space. This strategy have two advantages: the motion estimation leads to an efficient allocation of the search space, and the pose estimation method is adaptive to various kinds of motion.