• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.5
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• pp.1-11
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• 2004

In this paper we proposed a hierarchical ASM for real-time tracking of non-rigid objects. For tracking an object we used ASM for estimating object contour possibly with occlusion. Moreover, to reduce the processing time we used hierarchical approach for real-time tacking. In the next frame we estimated the initial feature point by using Kalman filter. We also added block matching algorithm for increasing accuracy of the estimation. The proposed hierarchical, prediction-based approach was proven to out perform the exiting non-hierarchical, non-prediction methods.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.38 no.2
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• pp.27-32
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• 2001

In this paper, the three dimension scanner system employing the parallel camera model is discussed. The camera calibration process and the three dimension scanning algorithm are developed. The laser strip line is utilized for assisting stereo matching. An object being scanned rotates on the plate which is activated by a stepping motor, The world coordinate which is. the measured distance from the camera to the object is converted into the model coordinate. The facets created from the point. cloud of the model coordinate is used for rendering the scanned model by using the graphic library such as OpenGL. The unmatched points having no validate matching points are interpolated from the validate matching points of the vicinity epipolar lines.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.11
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• pp.68-78
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• 1999

A new algorithm for tracking feature points in an image sequence is presented. Most existing feature tracking algorithms often produce false trajectories, because the matching measures do not precisely reflect motion characteristics. In this paper, three attributes including spatial coordinate, motion direction and motion magnitude are used to calculate the feature point correspondence. The trajectories of feature points are determined by calculation the matching measure, which is defined as the minimum weighted Euclidean distance between two feature points. The weights of the attributes are updated reflecting the motion characteristics, so that the robust tracking of feature points is achieved. The proposed algorithm can find the trajectories correctly which has been shown by experimental results.

• Proceedings of the KIEE Conference
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• 2002.11c
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• pp.159-162
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• 2002

This paper presents a modified localization scheme of a mobile robot. When it navigates, the position error of a robot is increased and doesn't go to a goal point where the robot intends to go at the beginning. The objective of localization is to estimate the position of a robot precisely. Many algorithms were developed and still are being researched for localization of a mobile robot at present. Among them, a localization algorithm named continuous localization proposed by Schultz has some merits on real-time navigation and is easy to be implemented compared to other localization schemes. Continuous Localization (CL) is based on map-matching algorithm with global and local maps using only ultrasonic sensors for making grid maps. However, CL has some problems in the process of searching the best-scored-map, when it is applied to a mobile robot. We here propose fast and powerful map-matching algorithm for localization of a mobile robot by experiments.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2002.05a
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• pp.608-612
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• 2002

An automatic face and facial feature points(FFPs) detection system is proposed. A face is represented as a graph where the nodes are placed at facial feature points(FFPs) labeled by their Gabor features md the edges are describes their spatial relations. An innovative flexible feature matching is proposed to perform features correspondence between models and the input image. This matching model works likes random diffusion process in the image spare by employing the locally competitive and globally corporative mechanism. The system works nicely on the face images under complicated background, pose variations and distorted by facial accessories. We demonstrate the benefits of our approach by its implementation on the fare identification system.

• Smart Structures and Systems
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• v.17 no.6
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• pp.935-956
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• 2016

With the help of advanced image acquisition and processing technology, the vision-based measurement methods have been broadly applied to implement the structural monitoring and condition identification of civil engineering structures. Many noncontact approaches enabled by different digital image processing algorithms are developed to overcome the problems in conventional structural dynamic displacement measurement. This paper presents three kinds of image processing algorithms for structural dynamic displacement measurement, i.e., the grayscale pattern matching (GPM) algorithm, the color pattern matching (CPM) algorithm, and the mean shift tracking (MST) algorithm. A vision-based system programmed with the three image processing algorithms is developed for multi-point structural dynamic displacement measurement. The dynamic displacement time histories of multiple vision points are simultaneously measured by the vision-based system and the magnetostrictive displacement sensor (MDS) during the laboratory shaking table tests of a three-story steel frame model. The comparative analysis results indicate that the developed vision-based system exhibits excellent performance in structural dynamic displacement measurement by use of the three different image processing algorithms. The field application experiments are also carried out on an arch bridge for the measurement of displacement influence lines during the loading tests to validate the effectiveness of the vision-based system.

• Proceedings of the KOSOMBE Conference
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• v.1996 no.05
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• pp.31-35
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• 1996

This paper presents a real time algorithm for monitoring of the arrythmia of ECG signal. A real time monitoring, following by detecting a QRS complex, is the most important. Using 2-dimensional time-delay coordinates which are reconstructed by the phase portrait plotting special trajectory, we detect QRS complexes. In this study, arrythmias are detected by matching the past standard template with tile present pattern when changing abruptly In order to matching with each other, we propose modified chain coding algorithm which applies vetor table consisting of eight orthonormal code(=binary code) to the phase portraits. This algorithm using logical function increases the weight if exceeding to the threshold determinded by correlation value and the distance from a straight line(y=x). Evaluating the performance of the proposed algorithm, we use standard MIT/BIH database. The results are fellowing, 1) Improve the speed of matching template than that of cross-correlation ever has been used. 2) Because the proposed algorithm is robust to varing fiducial point, it is possible to monitor the ECG signal with irregular RR interval. 3) In spite of baseline wandering owing to the low frequency noise, monitoring performance is not reduced.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.7
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• pp.1429-1436
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• 2009

In this paper, we propose a robust eye detection method using template matching based on genetic algorithm in the single facial image. The previous works for detecting pupil using genetic algorithm had a problem that the detection accuracy is influnced much by the initial population for it's random value. Therefore, their detection result is not consistent. In order to overcome this point we extract local minima in the facial image and generate initial populations using ones that have high fitness with a template. Each chromosome consists of geometrical informations for the template image. Eye position is detected by template matching. Experiment results verify that the proposed eye detection method improve the precision rate and high accuracy in the single facial image.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.18 no.8
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• pp.98-103
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• 2019

A more accurate method of feature point extraction and matching for three-dimensional reconstruction using low-resolution images of crops is proposed herein. This method is important in basic computer vision. In addition to three-dimensional reconstruction from exact matching, map-making and camera location information such as simultaneous localization and mapping can be calculated. The results of this study suggest applicable methods for low-resolution images that produce accurate results. This is expected to contribute to a system that measures crop growth condition.

• The Journal of Korea Robotics Society
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• v.16 no.4
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• pp.299-305
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• 2021

In this study, the task of robotic tidy-up is to clean the current environment up exactly like a target image. To perform a tidy-up task using a robot, it is necessary to estimate the pose of various objects and to classify the objects. Pose estimation requires the CAD model of an object, but these models of most objects in daily life are not available. Therefore, this study proposes an algorithm that uses point cloud and PCA to estimate the pose of objects without the help of CAD models in cluttered environments. In addition, objects are usually detected using a deep learning-based object detection. However, this method has a limitation in that only the learned objects can be recognized, and it may take a long time to learn. This study proposes an image matching based on few-shot learning and Siamese network. It was shown from experiments that the proposed method can be effectively applied to the robotic tidy-up system, which showed a success rate of 85% in the tidy-up task.