• Proceedings of the Korea Society for Simulation Conference
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• 1998.10a
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• pp.120-123
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• 1998

In animating an articulated entity with motion capture data, especially when the reconstruction is based on forward kinematics, there could be large discrepancies at the end effector. The small errors in joint angles tend to be amplified as the forward kinematics positioning progresses toward the end effector. In this paper, we present an algorithm that enhances the motion capture data to reduce positional errors at the end effector. The process is optimized so that the characteristics of the original joint angle data is preserved in the resulting motion. The frames at which the end-effector position needs to be accurate are designated as“keyframes”(e.g. starting and ending frames). In the algorithm, corrections by inverse kinematics are performed at sparse keyframes and they are interpolated with a cubic spline which produces a curve best approximating the measured joint angles. The experiment proves that our algorithm is a valuable tool to improve measured motion especially when end-effector trajectory contains a special goal.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.17 no.3
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• pp.197-203
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• 1999

Depending on geographical features and error sources in the survey field, inaccurate data is inevitable in GPS kinematic survey for positioning with feature codes. In this study, the trimmed mean and the first order differential equation are used to develop an inaccurate positioning data detection algorithm, and a cubic spline curve and a linear polynomial are used to interpolate the inaccurate data. Based on interpolated data, a digital map for 30 km range of rural highway is produced and a corresponding GIS coverage map is obtained by analyzing and solving the problem associated with the map.

• Journal of Korea Multimedia Society
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• v.16 no.2
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• pp.147-159
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• 2013

In medical visualization, volume visualization is widely used. Applying 3D images to diagnose requires high resolution and accurately implement visualization techniques are being researched accordingly. However, when a three-dimensional image volume visualization is implemented using volume data, aliasing will occur since using discrete data. Supersampling method, getting lots of samples, is used to reduce artifacts. One of the supersampling methods is Catmull-rom spline. This method calculates accurate interpolation value because it is easy to compute and pass through control points. But, Catmull-rom spline method occurs overshoot or undershoot in large gradient of pixel values. So, interpolated values are different from original signal. In this paper, we propose an adaptive adjusting weights interpolation method using Gaussian function. Proposed method shows that overshoot is reduced on the point has a large gradient and PSNR is higher than other interpolated image results.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.43 no.6 s.312
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• pp.92-100
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• 2006

In imaging devices such as digital cameras using a single image sensor, captured images are the sub-sampled images comprised of the pixels that have only one of the three primary colors per a pixel. This images should be restored to the color images through an image processing referred as color interpolation. In this paper, we derive relation between the average of the data from CFA image sensor and the average of each color channel data. By using this relation, a new efficient method for color interpolation is proposed. Also, in order to reduce the zipper effect in a restored image, missing luminance values are interpolated along any edges in the captured image. On the other hand, for the chrominance channel interpolation, we average difference between a chrominance value and a luminance value in a local area, and this average value is added to the pixel value of the interpolated location. The proposed method has been compared with several previous methods, and our experimental results show the better results than the other methods.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.2
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• pp.86-94
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• 2010

In this paper, we propose spatially adaptive color demosaicing of noisy Bayer data. When sensor noises are not considered in demosaicing, they may degrade result image. In order to obtain high resolution image, sensor noises are considered in the color demosaicing step. We identify flat, edge and pattern regions at each pixel location to improve the performance of the algorithm and to reduce complexity. Based on the pre-classified regions, the demosaicing of the G channel is performed using the local statistics to reduce the interpolation error. The sensor noise is simultaneously removed by a modified version of non-local mean filter in the green and in the color difference domain. The R and B channels are interpolated easily using fully interpolated and denoised G and color difference values. Experimental results show that the proposed method achieves a significant improvement in terms of visual and numerical criteria, when compared to conventional methods.

• Journal of the Korean Society for Precision Engineering
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• v.19 no.11
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• pp.160-166
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• 2002

In this paper, data acquisition and analysis of a measuring machine for marine engine's cams is discussed. A rotary encoder and linear scale of the machine to measure angular and linear displacement respectively are interfaced to the PC via encoder board with 2 channels. The design and measuring data are interpolated by cubic spline curves to compute the precision error which is defined by the maximum and minimum distances between two curves. The minimum zone fit of ISO is employed to evaluate the geometric deviation. The developed system takes only 5 minutes to measure and analyze while the CMM takes over 1 hours even with a skilled operator.

• Proceedings of the IEEK Conference
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• 2000.11c
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• pp.89-92
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• 2000

The wireless network has bursty and high error rates. Due to the quite limited bandwidth in wireless networks, images are usually transmitted as a compressed version with VLC(variable length coding). Loss of coded data can affect a decoded image to a large extent, making concealment of errors caused by data loss an important issue. This paper presents a error concealment technique for DCT(Discrete Cosine Transform) based image coding. First, a method to estimate the missing DC coefficients of a JPEG coded image which is required for decoding the compressed image, is suggested and evaluated. Second, the missing data is interpolated by exploiting the probability of being nonzero and the correlation between adjacent blocks. In addition, since the these technique is computational efficient, it conserves system resources and power consumption, which are restrictive in mobile computers.

• International Journal of Precision Engineering and Manufacturing
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• v.5 no.4
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• pp.21-27
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• 2004

In this paper, data acquisition and analysis of a measuring machine for marine engine's cams are discussed. A rotary encoder and linear scale of the machine to measure angular and linear displacement, respectively, are interfaced to the PC via an encoder board with 2 channels. The design and measuring data are interpolated by cubic spline curves to compute the precision error which is defined by the maximum and minimum distances between two curves. The minimum zone fit of ISO is employed to evaluate the geometric deviation. The developed system takes only 5 minutes to measure and analyze the precision error while the CMM takes over I hours even with a skilled operator.

• Journal of Korea Society of Digital Industry and Information Management
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• v.11 no.4
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• pp.155-164
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• 2015

In this paper, we propose a new color interpolation method based on trilateral filter approach, which not only preserve the high-frequency components(image edge) while interpolating the missing raw data of color image(bayer data pattern), but also immune to the image noise components and better preserve the detail of the low-frequency components. The method is the trilateral filter approach applying a gradient to the low frequency components of the image signal in order to preserve the high-frequency components and the detail of the low-frequency components through the measure of the freedom of similarity among adjacent pixels. And also we perform Gaussian smoothing to the interpolated image data in order to robust to the noise. In this paper, we compare the conventional demosaicing algorithm and the proposed algorithm using 10 test images in terms of hue MAD, saturation MAD and CPSNR for the objective evaluation, and verify the performance of the proposed algorithm.

• Korean Journal of Agricultural and Forest Meteorology
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• v.6 no.4
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• pp.272-289
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• 2004

The spatial resolution of local weather and climate information for agronomic practices exceeds the current weather service scale. To supplement the insufficient spatial resolution of official forecasts and observations, gridded climate data are frequently generated. Most ecological models can be run using gridded climate data to produce ecosystem responses at landscape scales. In this lecture, state of the art techniques derived from geospatial climatology, which can generate gridded climate data by spatially interpolating point observations at synoptic weather stations, will be introduced. Removal of the urban effects embedded in the interpolated surfaces of daily minimum temperature, incorporation of local geographic potential for cold air accumulation into the minimum temperature interpolation scheme, and solar irradiance correction for daytime hourly temperature estimation are presented. Some experiences obtained from their application to real landscapes will be described.