• Proceedings of the Korea Multimedia Society Conference
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• 2012.05a
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• pp.116-119
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• 2012

본 연구는 3D레이저 스캔 방식으로 계측된 인체 데이터를 대상으로 하여 인체의 여러 동작들에 대한 애니메이션 모듈 구현을 목표로 하였다. 이를 위하여 애니메이션 회전을 위한 기준점인 인체의 골격 기준점을 추출하고 추출된 기준점을 이용하여 골격을 잡고 각 골격에 따른 계층트리를 구성하였다. 구성된 계층트리의 골격에 해당되는 오브젝트 정점들을 골격과 연결하고 주어진 애니메이션 3차원 정점들에 행동 패턴을 적용하여 스캔데이터에 애니메이션을 구현하였다.

• Korean Journal of Computational Design and Engineering
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• v.10 no.3
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• pp.162-167
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• 2005

A 3D solid element mesh generation algorithm was newly developed. 3D surface points of global rectangular coordinates were supplied by a 3D laser scanner. The algorithm is strait forward and simple but it generates hexahedral solid elements. Then, the surface rectangular elements were generated from the solid elements. The key of the algorithm is elimination of unnecessary elements and 3D boundary surface fitting using given 3D surface point data.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2009.04a
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• pp.163-167
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• 2009

A discussion of a method that has been used with success in terrain modelling to estimate the height at any point on the land surface from irregularly distributed samples. The special requirements of terrain modelling are discussed as well as a detailed description of the algorithm and an example of its application.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2301-2306
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• 2005

Even if there are lots of researches on localization using 2D range finder in static environment, very few researches have been reported for robust real-time localization of mobile robot in uncertain and dynamic environment. In this paper, we present a new localization method based on ICP(Iterative Closest Point) algorithm for navigation of mobile robot under dynamic or uncertain environment. The ICP method is widely used for geometric alignment of three-dimensional models when an initial estimate of the relative pose is known. We use the method to align global map with 2D scanned data from range finder. The proposed algorithm accelerates the processing time by uniformly sampling the line fitted data from world map of mobile robot. A data filtering method is also used for threshold of occluded data from the range finder sensor. The effectiveness of the proposed method has been demonstrated through computer simulation and experiment in an office environment.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.669-670
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• 2015

Efficient management of the construction heavy equipment is required to reduce the rate of carbon emissions and on-site accidents. The intelligent excavation system (IES) will improve the construction quality and productivity through information technologies and efficient equipment operation, especially in large earthwork projects. Three-dimensional digitized ground data should be required for identifying the path of heavy equipment and work-site environment. Rapid development of terrain laser scanners (TLS) is more readily to acquire the digital data. This study suggests the '3D ground terrain processing platform (3DGTPP)' including data manipulating module and analyzing module of the scanned data for intelligent earthmoving equipment operation. The processing platform consists of six modules, including scanning, registering, manipulating, analyzing, transmitting, and storing. 3D ground terrain processing platform presented in this study will provide fundamental information for intelligent excavation system (IES), which will increase the efficiency of earthworks and safety of workers in significant.

• Journal of the Institute of Convergence Signal Processing
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• v.4 no.4
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• pp.15-22
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• 2003

A film scanner is one of the input devices for ac acquiring high resolution and high qualify of digital images from the existing optical film. Recently the demand of film scanners have risen for experts of image printing and editing fields. However, due to the nonlinear characteristic of light source and sensor, colors of the original film image do not correspond to the colors of the scanned image. Therefore color correction for the scanned digital image is essential in film scanner. In this paper, neural network method is applied for the color correction to CIE L/sup *//a/sup *//b/sup */ color model data converted from RGB color model data. Also a film scanner hardware with 12 bit color resolution for each R, G, B and 2400 dpi is implemented by using the TMS320C32 DSP chip and high resolution line sensor. An experimental result shows that the average color correction rate is 79.8%, which is an improvement of 43.5% than our previous method, polygonal regression method.

• Journal of Technologic Dentistry
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• v.37 no.4
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• pp.191-197
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• 2015

Purpose: The purpose of this study was to compare the accuracy of the scan data acquired by the extra-oral and intra-oral scanner. Methods: The maxillary right first molar was made of polymethyl methacrylate(PMMA) specimen. This PMMA specimen was scanned with a engineering scanner and intra-oral scanner. Meanwhile, extra-oral scanner scanned stone die duplicated from PMMA master die. Trueness and precision of scan datas was measured by 3-dimensinal inspection. Independent t-test was conduct to analysis the significant difference(a=0.05). Results: In the trueness analysis, mean of discrepancies were 13.82um for intra oral scanner and 16.84 um for extra-oral scanner. In the precision analysis, mean of discrepancies were 11.72 for inta-oral scanner and 9.2 for extra-oral scanner. Both trueness and precision showed a statistically significant difference (Table 1, p<0.05). Conclusion: Intra-oral scanner can show higher trueness than extra-oral scanner, it has lower precision.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.1
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• pp.95-99
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• 2018

In this paper, we propose an efficient pixel value prediction algorithm that can accurately predict pixel value using neighboring pixel values scanned in reverse s-order in the image. Generally, image has similarity with similar values between adjacent pixel values, and may have directional edge characteristics. In this paper, we proposed a method to improve pixel value prediction accuracy by improving GAP(Gradient Adjacent Pixel) algorithm for predicting pixel value by using similarity between adjacent pixels and edge characteristics. The proposed method increases the accuracy of the predicted pixel value by precisely predicting the pixel value using the positional weights of the neighboring pixels. Experiments on real images confirmed the superiority of the proposed algorithm. The proposed algorithm is useful for applications such as reversible data hiding, reversible watermarking, and data compression applications.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.40 no.1
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• pp.43-50
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• 2003

Today, the demand of image acquisition systems grows as the multimedia applications go on increasing greatly. Among the systems, film scanner is one of the systems, which can acquire high quality and high resolution images. However due to the nonlinear characteristic of the light source and sensor, colors of the original film image do not correspond to the colors of the scanned image. Therefore color correction mr the scanned digital image is essential in the film scanner. In this paper, polynomial regression method is applied for the color correction to CIE $L^{*}$ $a^{*}$ $b^{*}$ color model data converted from RGB color model data. A1so a film scanner hardware with 12 bit color resolution for each R, G, B and 2400 dpi was implemented by using TMS320C32 DSP chip and high resolution line sensor. An experimental result shows that the average color difference ($\Delta$ $E^{*}$$_{ab}$ ) is reduced from13.48 to 8.46.6.6.6.6.

• Journal of Biosystems Engineering
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• v.40 no.2
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• pp.153-158
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• 2015

Purpose: The research presented in this paper applied the chemometric analysis to the near-infrared spectral data from line-scanned hyperspectral images of beef and fish meals in animal feeds. The chemometric statistical models were developed to distinguish beef meals from fish ones. Methods: The meal samples of 40 fish meals and 15 beef meals were line-scanned to obtain hyperspectral images. The spectral data were retrieved from each of 3600 pixels in the Region of Interest (ROI) of every sample image. The wavebands spanning 969 nm to 1551 nm (across 176 spectral bands) were selected for chemometric analysis. The partial least squares regression (PLSR) and the principal component analysis (PCA) methods of the chemometric analysis were applied to the model development. The purpose of the models was to correctly classify as many beef pixels as possible while misclassified fish pixels in an acceptable amount. Results: The results showed that the success classification rates were 97.9% for beef samples and 99.4% for fish samples by the PLSR model, and 85.1% for beef samples and 88.2% for fish samples by the PCA model. Conclusion: The chemometric analysis-based PLSR and PCA models for the hyperspectral image analysis could differentiate beef meals from fish ones in animal feeds.