• Journal of the Institute of Electronics Engineers of Korea CI
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• v.43 no.1 s.307
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• pp.45-52
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• 2006

In this paper, a real-time stereoscopic image conversion method using a single frame from a 2-D image is proposed. The Stereoscopic image is generated by creating depth map using vortical position information and parallax processing. For a real-time processing of stereoscopic conversion and reduction of hardware complexity, it uses image sampling, object segmentation by standardizing luminance and depth map generation by boundary scan. The proposed method offers realistic 3-D effect regardless of the direction, velocity and scene conversion of the 2-D image. It offers effective stereoscopic conversion using images suitable conditions assumed in this paper such as recorded image at long distance, landscape and panorama photo because it creates different depth sense using vertical position information from a single frame. The proposed method can be applied to still image because it uses a single frame from a 2-D image. The proposed method has been evaluated using visual test and APD for comparing the stereoscopic image of the proposed method with that of MTD. It is confirmed that stereoscopic images conversed by the proposed method offers 3-D effect regardless of the direction and velocity of the 2-D image.

• Journal of The Korean Association For Science Education
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• v.30 no.8
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• pp.1031-1043
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• 2010

The purpose of this study was to develop the brain compatibility index equation for the brain-based analysis method of science teaching-learning program. To develop the index equation, one sample unit in middle school science programs was selected and analyzed by the brain-based analysis frame (CORE Brain Map). Then, the index equation was derived by the CORE Brain Map. In addition, four sample units in elementary science programs were selected to validate the brain compatibleness index equation. From the random network theory of Erdos and Renyi, this study derived the brain compatibility index equation; (BCI=$\frac{L_o}{11(N_o-1)}{\cdot}{\sum}\limits_{i=1}^4l_iw_i$) for quantitative analysis of science teaching-learning program. With this equation, this study could find the quantitative difference among the teaching-learning programs through the unit and curriculum. Brain-based analysis methods for the qualitative and quantitative analysis of science teaching-learning program, which was developed in this study is expected, to be a useful application to analyze and diagnose various science teaching-learning programs.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.49 no.12
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• pp.651-658
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• 2000

This paper presents a new method to extract traffic information such as number of passing vehicles and average speed by a pair of stereo road images. The whole process consists of the extraction of vehicles and the tracking of the extracted vehicles. For the extraction of vehicles, the outline of each vehicle is obtained by using binary region growing technique applied to disparity map based on multi-resolution stereo matching. The Kalman filter tracking algorithm is applied to the extracted vehicle outlines to determine the flow of vehicles. Experimental results show that the proposed method significantly improved recognition rate of vehicles over the conventional methods-frame difference and background elimination methods.

• Journal of Korea Multimedia Society
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• v.22 no.2
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• pp.311-321
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• 2019

Virtual reality applications in Head-Mounted Displays require high frame rates and low latency rendering techniques. Ray tracing offers many benefits, such as high-quality image generation, but has not been utilized due to lower performance than rasterization. But that can obtain good result combined with gaze-tracking technology and human visual system's operation principle. In this paper, we propose a method to optimize the foveated sampling map and to maintain the visual quality through the fast voronoi nearest interpolation. The proposed method further reduces the computational cost that has been improved by the previous foveated sampling. It also smoothes the voronoi boundary using adaptive sibson interpolation, which was not possible in real-time. As a result, the proposed method can render real-time high-quality images with low visual difference.

• Journal of the Korean Institute of Telematics and Electronics
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• v.23 no.2
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• pp.206-216
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• 1986

In this paper, the moving distance and velocity of a single moving object are measured by sampling three frames in a two-dimensional line sequence image. The brightness of each frame is analyzed, and the bit data of their pixel are rearranged so that the difference image may be extracted. The parameters for recognition of the object are the gray level of the object, the number of vertex points and the distance between the vertex points. The moving distance obtained from the coordinate which is constructed by the bit processing of the data in the memory map of a microcomputer, and the moving velocity is obtained from the moving distance and the time interval between the first and second sampled frames.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.1
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• pp.145-152
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• 2019

In this paper, we proposed a shaking image stabilization algorithm using deep learning. The proposed algorithm utilizes deep learning, unlike some 2D, 2.5D and 3D based stabilization techniques. The proposed algorithm is an algorithm that extracts and compares features of shaky images through CNN network structure and LSTM network structure, and transforms images in reverse order of movement size and direction of feature points through the difference of feature point between previous frame and current frame. The algorithm for stabilizing the shake is implemented by using CNN network and LSTM structure using Tensorflow for feature extraction and comparison of each frame. Image stabilization is implemented by using OpenCV open source. Experimental results show that the proposed algorithm can be used to stabilize the camera shake stability in the up, down, left, and right shaking images.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.11C
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• pp.940-947
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• 2010

Motion Compensated Frame Interpolation(MCFI) has been used to reduce motion jerkiness for dynamic scenes and motion blurriness for LCD-panel display as post processing for high quality display. However, MCFI that directly uses the motion information often suffers from annoying artifacts such as blockiness, ghost effects, and deformed structures. So in this paper, we propose a novel edge-based adaptively weighted vector median filter as post-processing. At first, the proposed method generates an edge direction map through a sobel mask and a weighted maximum frequent filter. And then, outlier MVs are removed by average of angle difference and replaced by a median MV of $3{\times}3$ window. Finally, weighted vector median filter adjusts the weighting values based on edge direction derived from spatial coherence between the edge direction continuity and motion vector. The results show that the performance of PSNR and SSIM are higher up to 0.5 ~ 1 dB and 0.4 ~ 0.8 %, respectively.

• Journal of the Korean Society of Marine Environment & Safety
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• v.25 no.2
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• pp.159-168
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• 2019

This study was designed to investigate the physiological response of humans to alcohol during underwater activity and to complete related risk analysis. After comparing human responses to alcohol during underwater activity, we analyzed physiological changes and risk level using a new risk analysis method developed in this study, 'Risk Assessment and Analysis (RAA)'. RAA is a modified method based on an internal control frame work. It has 3 steps, the first of which is to analyze risk correlation. The second step is to quantify risk and build a risk database. The last step is to analyze the diagramed risk map. Using RAA, the risk levels of alcohol use underwater were calculated and diagramed. The diagramed risk map was then used to analyze the difference between risk levels underwater before and after alcohol use. As a result, it was found that risk level underwater increased after alcohol use. This study shows alcohol use increases the ratio of high risk groups during underwater activity. It also indicates that risk levels can be quantified according to the likelihood and impairment scale, which can potentially help in identifying high risk groups for intensive management underwater.