• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.16 no.2
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• pp.177-185
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• 1998

There is an increasing request for 3D data and outlines on building for urban planning and design. This paper describes an approach to extract building using Digital Surface Models(DSM) and stereo pairs of aerial images. DSM contain informations not only about the topographic surface like Digital Elevation Models(DEM), but also about buildings and other objects higher than the surrounding topographic surface, e.g. tees. We therefore describe our approach consisting of two step procedures. The first step of the approach is to generate DSM by stereo matching using Maximum Likelihood Estimation and Dynamic Programming. The proposed stereo matching is using the cost function for finding the disparity between the left and right image, and the Dynamic Programming for solving the stereo matching problem. The second step is to detect building outlines using the DSM and the edge informations extracted from a digital aerial image by Sobel Operator. The overlay analysis of the DSM and the edge information by Sobel Operator was efficient to detect building outlines.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.49 no.2
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• pp.8-17
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• 2012

In this paper we proposes a new framework to obtain 3D shape information of thin film rapidly. The conventional equipments based on reflectometry are not suitable for obtaining 3D overall shape information of thin film rapidly since they require more than 30 minutes to measure the absolute thickness for 170 points. The proposed framework is based on an image analysis method that extracts contour lines from interference fringes images using Canny edge detector. The absolute thickness for contour lines are measured and then a height map from the contour lines is obtained by interpolation using Borgefors distance transformation. The extracted height map is visualized using the DirectX 3D terrain rendering method. The proposed framework can provide 3D overall shape information of thin film in about 5 minutes since relatively small number of real measurement for contour lines is required.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.5
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• pp.28-34
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• 2007

A histogram-based road border line extractor is proposed for an efficient road extraction from the high-resolution satellite imagery. The road border lines are extracted from an edge strength map based on the directional histogram difference between the road and the non-road region. The straight and the curved roads are extracted hierarchically from the edge strength map of the original image and the segmented road cluster images, and the road network is constructed based on the connectivity. Unlike the conventional approaches based on the spectral similarity, the proposed road extraction method is more robust to noise because it extracts roads based on the histogram, and is able to extract both the location and the width of roads. In addition, the proposed method can extract roads with various spectral characteristics by identifying the road clusters automatically. Experimental results on IKONOS multi-spectral satellite imagery with high spatial resolution show that the proposed method can extract the straight and the curved roads as well as the accurate road border lines.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.05a
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• pp.661-663
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• 2016

Corruption occurs in the process of processing image signal and the corruption changes the pixel value within the image to damage the original information. AWGN(additive white Gaussian noise) is a representative example. For filters to remove AWGN, there are filters such as MF(mean filter), WF(wiener filter), and AWMF(adaptive weighted mean filter). However images processed through standard previous filters lock preservation characteristics in edge areas. Therefore, threshold value is applied for processing on the standard deviation of the local mask in this study and if the standard deviation is smaller than the threshold value, it is not filtered and if the value is bigger than the threshold value, the study suggested an algorithm that processes using weighted value utilizing standard deviation.

• Journal of Digital Contents Society
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• v.18 no.8
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• pp.1517-1522
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• 2017

Among single image SR techniques, the TV based SR approach seems most successful in terms of edge preservation and no artifacts. But, this approach achieves insufficient SR for texture component. In this paper, we proposed a new TV-G decomposition based SR method to solve this problem. We proposed the SVR based up-sampling to get better edge preservation in the structure component. The NNE used the relaxed constraint to improve the NE. We used the NNE based learning method to improve the resolution of the texture component. Through experimental results, we quantitatively and qualitatively confirm the improved results of the proposed SR method when comparing with conventional interpolation method, ScSR, TV and NNE.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.7
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• pp.81-89
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• 1999

Image obtained by incomplete communication always include noise, blur and distortion, etc. In this paper, we propose and apply the new spatial filter algorithm, called an optimal adaptive generalized stack filter(AGSF), which optimizes adaptive generalized stack filter(AGSF) using neural network weight learning algorithm of back-propagation learning algorithm for improving noise removal and edge preservation rate. AGSF divides into two parts: generalized stack filter(GSF) and adaptive multistage median filter(AMMF), GSF improves the ability of stack filter algorithm and AMMF proposes the improved algorithm for reserving the sharp edge. Applied to neural network theory, the proposed algorithm improves the performance of the AGSF using two weight learning algorithms, such as the least mean absolute(LAM) and least mean square (LMS) algorithms. Simulation results of the proposed filter algorithm are presented and discussed.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.6
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• pp.705-711
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• 2011

This paper proposes an effective algorithm of license plate recognition for industrial applications. By applying Canny edge detection on a vehicle image, it is possible to find a connected rectangular, which is a strong candidate for license plate. The color information of license plate separates plates into white and green. Then, OTSU binary image processing and foreground neighbor pixel propagation algorithm CLNF will be applied to each license plates to reduce noise except numbers and letters. Finally, through labeling, numbers and letters will be extracted from the license plate. Letter and number regions, separated from the plate, pass through mesh method and thinning process for extracting feature vectors by X-Y projection method. The extracted feature vectors are compared with the pre-learned weighting values by backpropagation neural network to execute final recognition process. The experiment results show that the proposed license plate recognition algorithm works effectively.

• Smart Media Journal
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• v.5 no.1
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• pp.15-23
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• 2016

This paper proposes an effective algorithm of Korean license plate recognition. By applying Haar-like feature and Canny edge detection on a captured vehicle image, it is possible to find a connected rectangular, which is a strong candidate for license plate. The color information of license plate separates plates into white and green. Then, OTSU binary image processing and foreground neighbor pixel propagation algorithm CLNF will be applied to each license plates to reduce noise except numbers and letters. Finally, through labeling, numbers and letters will be extracted from the license plate. Letter and number regions, separated from the plate, pass through mesh method and thinning process for extracting feature vectors by X-Y projection method. The extracted feature vectors are classified using neural networks trained by backpropagation algorithm to execute final recognition process. The experiment results show that the proposed license plate recognition algorithm works effectively.

• Journal of Broadcast Engineering
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• v.8 no.2
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• pp.181-197
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• 2003

Notion Compensation(MC) technique using Sub-Band Coding with the hierarchical structure is efficient to estimate real motion. In the hierarchical pyramid method, low-band MC pyramid method is popular, where the upper layer estimate the glover motion and next lower layer estimate the local motion. The low-band MC pyramid scheme has two problems. First, because the quantization errors at lower layer are accumulated when using coding and quantizing, it is impossible to search the exact Motion Vector(MV) Second, because of the top-down search problem in the hierarchical structure, MV mismatch in upper layer causes serious MV in lower layer So. we propose new hierarchical MC pyramid method based on edge classification. In this Paper, we show that the performance of proposed Pass-band motion compensation pyramid technique is better than low-band motion compensation pyramid. Also, in the pyramid motion estimation, we propose initial MV estimation scheme based on the edge-pattern classification. As a result, we find that PSNR was increased.

• Journal of Biomedical Engineering Research
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• v.29 no.3
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• pp.212-221
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• 2008

The total hip replacement (THR) has been used as the most effective way to restore the function of damaged hip joint. However, various factors have caused some side effects after the THR. Unfortunately, the success of the THR have been decided only by the proficiency of surgeons so far. Hence, It is necessary to find the way to minimize the side effect caused by those factors. The purpose of this study was to suggest the definite data, which can be used to design and choose the optimal hip implant. Using finite element analysis (FEA), the biomechanical condition of bone cement was evaluated. Stress patterns were analyzed in three conditions: cement mantle, procimal femur and stem-cement contact surface. Additionally, micro-motion was analyzed in the stem-cement contact surface. The 3-D femur model was reconstructed from 2-D computerized tomography (CT) images. Raw CT images were preprocessed by image processing technique (i.e. edge detection). In this study, automated edge detection system was created by MATLAB coding for effective and rapid image processing. The 3-D femur model was reconstructed based on anatomical parameters. The stem shape was designed using that parameters. The analysis of the finite element models was performed with the variation of parameters. The biomechanical influence of each parameter was analyzed and derived optimal parameters. Moreover, the results of FE A using commercial stem model (Zimmer's V erSys) were similar to the results of stem model that was used in this study. Through the study, the improved designs and optimal factors for clinical application were suggested. We expect that the results can suggest solutions to minimize various side effects.