• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.5
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• pp.1080-1088
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• 2004

In this paper, the interesting moving objects tracking algorithm using color information on Multi-Video camera against variance of intensity, shape and background is proposed. Moving objects are detected by using difference image method and integral projection method to background image and objects image only with hue area, after converting RGB color coordination of image which is input from multi-video camera into HSI color coordination. Hue information of the detected moving area are segmented to 24 levels from $0^{\circ}$ to $360^{\circ}$. It is used to the feature parameter of the moving objects that are three segmented hue levels with the highest distribution and difference among three segmented hue levels. To examine propriety of the proposed method, human images with variance of intensity and shape and human images with variance of intensity, shape and background are targeted for moving objects. As surveillance results of the interesting human, hue distribution level variation of the detected interesting human at each camera is under 2 level, and it is confirmed that the interesting human is tracked and surveilled by using feature parameters at cameras, automatically.

• Journal of Korea Multimedia Society
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• v.13 no.10
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• pp.1474-1486
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• 2010

In this paper, we propose an algorithm which represents the distance depiction technique of real painting that named "Aerial Perspective" in painterly rendering. It is a painting technique that depicts the attenuations of light in the atmosphere, and the scattering effect is changed by the distance, altitude and density of atmospheres. For the reflection of these natures, we use the depth information corresponding to an input image and user-defined parameters, so that user changes the effect level. We calculate the distance and altitude of every pixel with the depth information and parameters about shot information, and control the scattering effects by expression parameters. Additionally, we accentuate the occluding edges detected by the depth information to clarify the sense of distance between fore and back-ground. We apply our algorithm on various landscape scenes, and generate the distance-emphasized results compared to existing works.

• Journal of KIBIM
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• v.12 no.4
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• pp.19-31
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• 2022

With the development of 3D-based CAD (Computer Aided Design), attempts at freeform building design have expanded to small and medium-sized buildings in Korea. However, a standardized system for continuous utilization of shape data and BIM conversion process implemented with 3D-based NURBS is still immature. Without accurate review and management throughout the Freeform building project, interference between members occurs and the cost of the project increases. This is very detrimental to the project. To solve this problem, we proposed a continuous utilization process of 3D shape information based on BIM parameters. Our process includes algorithms such as Auto Split, Panel Optimization, Excel extraction based on shape information, BIM modeling through Adaptive Component, and BIM model utilization method using ID Code. The optimal cutting reference point was calculated and the optimal material specification was derived using the Panel Optimization algorithm. With the Adaptive Component design methodology, a BIM model conforming to the standard cross-section details and specifications was uniformly established. The automatic BIM conversion algorithm of shape data through Excel extraction created a BIM model without omission of data based on the optimized panel cutting reference point and cutting line. Finally, we analyzed how to use the BIM model built for automatic conversion. As a result of the analysis, in addition to the BIM utilization plan in the general construction stage such as visualization, interference review, quantity calculation, and construction simulation, an individual management plan for the unit panel was derived through ID data input. This study suggested an improvement process by linking the existing research on atypical panel optimization and the study of parameter-based BIM information management method. And it showed that it can solve the problems of existing Freeform building project.

• Structural Engineering and Mechanics
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• v.86 no.5
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• pp.673-686
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• 2023

Determining the properties of pile from cone penetration test (CPT) is costly, and need several in-situ tests. At the present study, two novel hybrid learning models, namely PSO-RF and HHO-RF, which are an amalgamation of random forest (RF) with particle swarm optimization (PSO) and Harris hawks optimization (HHO) were developed and applied to predict the pile set-up parameter "A" from CPT for the design aim of the projects. To forecast the "A," CPT data along were collected from different sites in Louisiana, where the selected variables as input were plasticity index (PI), undrained shear strength (S_u), and over consolidation ratio (OCR). Results show that both PSO-RF and HHO-RF models have acceptable performance in predicting the set-up parameter "A," with R² larger than 0.9094, representing the admissible correlation between observed and predicted values. HHO-RF has better proficiency than the PSO-RF model, with R² and RMSE equal to 0.9328 and 0.0292 for the training phase and 0.9729 and 0.024 for testing data, respectively. Moreover, PI and OBJ indices are considered, in which the HHO-RF model has lower results which leads to outperforming this hybrid algorithm with respect to PSO-RF for predicting the pile set-up parameter "A," consequently being specified as the proposed model. Therefore, the results demonstrate the ability of the HHO algorithm in determining the optimal value of RF hyperparameters than PSO.

• Journal of Korea Society of Industrial Information Systems
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• v.19 no.4
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• pp.65-72
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• 2014

To improve the productivity of manufacturing company, the analysis of loss in shop floor has to be conducted and validated. This paper introduces the downtime tracking module using the pre-developed shop floor information acquisition system. To collect the downtime, it utilized shop floor monitoring information, user-registered downtime event, equipment diagnosis algorithm and operator's input. Also, it provided the user interface for the analysis of downtime. From the results of a pilot study, the usability of developed system was validated.

• The KIPS Transactions:PartB
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• v.11B no.1
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• pp.13-20
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• 2004

In the real-time automatic face recognition technique, accurate face detection is essential and very important part because it has the effect to face recognition performance. In this paper, we use color information, edge information, and binary information to detect candidate regions of eyes from Input image, and then detect face candidate region using the center point of the detected eyes. We verify both eye candidate region and face candidate region using Support Vector Machines(SVM). It is possible to perform fast and reliable face detection because we can protect false detection through these verification process. From the experimental results, we confirmed the Proposed algorithm in this paper shows excellent face detection rate over 99%.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.7 no.2
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• pp.106-110
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• 2014

This paper proposed the face recognition method which can be effectively applied to the robot's vision system. The proposed algorithm is recognition using hue extraction and feature point. hue extraction was using difference of skin color, pupil color, lips color. Features information were extraction from eye, nose and mouth using feature parameters of the difference between the feature point, distance ratio, angle, area. Feature parameters fuzzified data with the data generated by membership function, then evaluate the degree of similarity was the face recognition. The result of experiment are conducted with frontal color images of face as input images the received recognition rate of 96%.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.9
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• pp.165-170
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• 2014

Speech enhancement techniques that remove surrounding noise are stressed to preprocessor of speech recognition. Among the various speech enhancement techniques, Codebook-based Speech Enhancement (CBSE) operates efficiently in non-stationary noise environments. But, CBSE has some problems that inaccurate gains can be estimated if mismatch occur between input noisy signal and trained speech/noise codevectors. In this paper, the Normalized Weighting Factor (NWF) is calculated by long-term noise estimation algorithm based on Signal-to-Noise Ratio, compensated to the conventional inaccurate gains. The proposed CBSE shows better performance than conventional CBSE.

• Journal of Korea Society of Digital Industry and Information Management
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• v.8 no.2
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• pp.95-104
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• 2012

In this paper, an estimation of person height and 3D location of a moving person by using the pan/tilt-embedded stereo tracking system is suggested and implemented. In the proposed system, face coordinates of a target person is detected from the sequential input stereo image pairs by using the YCbCr color model and phase-type correlation methods and then, using this data as well as the geometric information of the stereo tracking system, distance to the target from the stereo camera and 3-dimensional location information of a target person are extracted. Basing on these extracted data the pan/tilt system embedded in the stereo camera is controlled to adaptively track a moving person and as a result, moving trajectory of a target person can be obtained. From some experiments using 780 frames of the sequential stereo image pairs, it is analyzed that standard deviation of the position displacement of the target in the horizontal and vertical directions after tracking is kept to be very low value of 1.5, 0.42 for 780 frames on average, and error ratio between the measured and computed 3D coordinate values of the target is also kept to be very low value of 0.5% on average. These good experimental results suggest a possibility of implementation of a new stereo target tracking system having a high degree of accuracy and a very fast response time with this proposed algorithm.

• The Journal of the Korea Contents Association
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• v.5 no.6
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• pp.378-385
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• 2005

Mistaking normal packets for harmful traffic may not offer service in conformity with the intention of attacker with harmful traffic, because it is not easy to classify network traffic for normal service and it for DDoS(Distributed Denial of Service) attack. And in the IPv6 environment these researches on harmful traffic are weak. In this dissertation, hosts in the IPv6 environment are attacked by NETWOX and their attack traffic is monitored, then the statistical information of the traffic is obtained from MIB(Management Information Base) objects used in the IPv6. By adapting the ESM(Exponential Smoothing Method) to this information, a normal traffic boundary, i.e., a threshold is determined. Input traffic over the threshold is thought of as attack traffic.