• Journal of the Korea Computer Industry Society
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• v.3 no.9
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• pp.1177-1188
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• 2002

To classify real time Lead pin images in this paper, The image acquisition system was composed to C.C.D, image frame grabber(DT3153), P.C(PentiumIII). I proposed image processing algorithms. This algorithms were composed to real time monitoring, Lead Pin image acquisition, image noise deletion, object area detection, point detection and pattern classification algorithm. The raw images were acquired from Lead pin images using the system. The result images were obtained from raw images by image processing algorithms. In implemental result, The right recognition was 97 of 100 acceptable products, 95 of 100 defective products. The recognition rate was 96% for total 200 Lead Pins.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.10 no.5
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• pp.229-235
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• 2010

In this paper, we propose a method to improve the efficiency of the moving object detection in real-time surveillance camera system. The existing methods, the methods using differential image and background image, are difficult to detect the moving object from outside the video streams. The proposed method keeps the background image if it doesn't be detected moving object using the differential value between a previous frame and a current frame. And the background image is renewed as the moving object is gone in a frame. To decide people and wild pig, the proposed system estimates a bounding box enclosing each moving object in the detecting region. As a result of simulation, the proposed method is better than the existing method.

• Journal of the Korea Society of Computer and Information
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• v.10 no.1 s.33
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• pp.223-229
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• 2005

In this paper a coarse-to-fine optical flow detection method is proposed. Provided that optical flow gives reliable approximation to two-dimensional image motion, it can be used to recover the three-dimensional motion, but usually to set the reliable optical flows are difficult. The proposed algorithm uses Horn's algorithm for detecting initial optical flow, then Thin Plate Spline is introduced to warp a image frame of the initial optical flow to the next image frame. The optical flow for the warped image frame is again used iteratively until the mean square error between two image sequence frames is lowered. The proposed method is experimented for the real moving picture image sequence. The proposed algorithm gives dense optical flow vectors.

• Smart Media Journal
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• v.9 no.4
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• pp.102-108
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• 2020

In this paper, we propose a real-time method of detecting hand motions and extracting the signal frame induced by EF(Electric Field) sensors. The signal induced by hand motion includes not only noises caused by various environmental sources as well as sensor's physical placement, but also different initial off-set conditions. Thus, it has been considered as a challenging problem to detect the motion signal and extract the motion frame automatically in real-time. In this study, we remove the PLN(Power Line Noise) using LPF with 10Hz cut-off and successively apply MA(Moving Average) filter to obtain clean and smooth input motion signals. To sense a hand motion, we use two thresholds(positive and negative thresholds) with offset value to detect a starting as well as an ending moment of the motion. Using this approach, we can achieve the correct motion detection rate over 98%. Once the final motion frame is determined, the motion signals are normalized to be used in next process of classification or recognition stage such as LSTN deep neural networks. Our experiment and analysis show that our proposed methods produce better than 98% performance in correct motion detection rate as well as in frame-matching rate.

• Proceedings of the IEEK Conference
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• 2001.09a
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• pp.179-182
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• 2001

In this paper. a key frame extraction algorithm for browsing and searching the summary of a video is proposed. Toward this end, important frames representing a shot are selected according to the correlations among frames. by using the Fourier descriptor which is useful for the shot boundary detection. To quantitatively evaluate the importance of selected frames. a new measure based on correlation coefficients of frames is proposed. If there are several frames with a same importance. another criteria is introduced to break the tie. by computing the partial moment of subframes including each candidate key frame so that the distortion rate is minimized Since a key frame extraction algorithm can be evaluated subjectively. the performance of the proposed algorithm has been verified by a statistical test. Experiments show that more than 20% improvement has been obtained by the proposed algorithm compared to existing methods.

• Proceedings of the KSR Conference
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• 2000.11a
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• pp.461-467
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• 2000

This study proposes the integrity evaluation of bogie frame using ultrasonic waves-fractography analysis. Analysis objectives in this study are to investigate fracture planes of damaged zone by the A-scan method. The surface condition of fracture plane shows degree of degradation by stress concentration. The detection of the natural defects in bogie frame is performed using the characteristics of echodynamic pattern in ultrasonic signal. Results of ultrasonic testing agree fairly well with those of actual fracture plane. In quantitative fractography analysis, microstructures of actual fracture plane turned out to be intergranular and transgranular fracture, Proposed ultrasonic-fractography analysis in this study can be used for the integrity evaluation of the bogie frame

• Journal of the Korean Society for Railway
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• v.8 no.5
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• pp.419-424
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• 2005

This paper has performed fatigue and nondestructive test of bogie frame for Korean tilting train. Before the fatigue test, static tests were carried out. From the test, the structural safety was investigated using Goodman diagram. After the static test, the fatigue test were conducted under tilting load conditions. The fatigue test was conducted for $10{\times}10^6$ cycles. During the fatigue test, the nondestructive tests using magnetic particle and liquid penetrant were performed at $6{\times}10^6$ cycle and $10{\times}10^6$cycle. From the crack detection tests, it was known that there was no fatigue crack in the bogie frame.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.21 no.4
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• pp.11-18
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• 2007

A moving object detection algorithm for surveillance video is here proposed which employs background initialization based on two-stage median filtering and a background updating method based on state transition diagram. In the background initialization, the spatiotemporal similarity is measured in the subinterval. From the accumulated difference between the base frame and the other frames in a subinterval, the regions affected by moving objects are located. The median is applied over the subsequence in the subinterval in which regions share similarity. The outputs from each subinterval are filtered by a two-stage median filter. The background of every frame is updated by the suggested state transition diagram The object is detected by the difference between the current frame and the updated background. The proposed method showed good results even for busy, crowded sequences which included moving objects from the first frame.

• Journal of the Korean Society for Railway
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• v.3 no.2
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• pp.77-83
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• 2000

This study proposes the integrity evaluation of the bogie frame using ultrasonic fractography analysis. Analysis objectives in this study are to investigate fracture planes of damaged zone by the A-scan method. The surface condition of fracture planes shows degree of degradation by the stress concentration. The detection of the natural defects in the bogie frame is performed using the characteristics of echodynamic pattern in ultrasonic signal. Results of ultrasonic testing agree fairly well with those of actual fracture plane. In quantitative fractography analysis, microstructures of actual fracture plane turned out to be intergranular and transgranular fracture. Proposed ultrasonic fractography analysis in this study can be used for the integrity evaluation of the bogie frame.

• Proceedings of the IEEK Conference
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• 2000.07b
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• pp.1049-1052
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• 2000

In this paper, an efficient method to find cut in the MPEG stream data is proposed. For this purpose, histogram difference and pixel difference is considered as a noise signal. The signal is then filtered out by a median filter to make the frame difference larger. The frame difference obtained in this way is classified into cut frame and non-cut frame by the 2-means clustering without using any threshold value. To improve the classification ratio, a back-propagation neural network is constructed, where outputs of 2-means clustering are used as the inputs of the network. The simulation results demonstrate the performance of the proposed methods.