• International Journal of Highway Engineering
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• v.10 no.2
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• pp.125-133
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• 2008

Achieving consistent geometric design is an important goal in highway design to ensure obtaining safe, economical and smooth traffic operation. Most evaluation of consistency is based on 'speed change' in speed profile. According to literature, the speed depends on geometric elements, speed on tangent section prior to a curve, and background around roads. Especially, the radius is the most main element mentioned in various literature. Therefore, this paper shows two ways of calculating horizontal radius on real road, that is, three-dimensional road. First of all, the radius of horizontal curve is calculated based on physical method. The calculated radius contains not only superelevation but also longitudinal grade while the current minimum radius is calculated by considering superelevation and side friction according to the point-mass equation. Secondly, the problem of composed curves with distorted appearance by overlaying sag or crest vertical alignment has been known. To quantify the extent of distortion effects, the method of calculation of real seen so called 'Perspective Radius' is developed. The paper presents the perspective radius and recommended perspective radius.

• Journal of Biosystems Engineering
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• v.17 no.1
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• pp.65-78
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• 1992

When using a computer vision system for a measurement, the geometrically distorted input image usually restricts the site and size of the measuring window. A geometrically distorted image caused by the image sensing and processing hardware degrades the accuracy of the visual measurement and prohibits the arbitrary selection of the measuring scope. Therefore, an image calibration is inevitable to improve the measuring accuracy. A calibration process is usually done via four steps such as measurement, modeling, parameter estimation, and compensation. In this paper, the efficient error calibration technique of a geometrically distorted input image was developed using a neural network. After calibrating a unit pixel, the distorted image was compensated by training CMLAN(Cerebellar Model Linear Associator Network) without modeling the behavior of any system element. The input/output training pairs for the network was obtained by processing the image of the devised sampled pattern. The generalization property of the network successfully compensates the distortion errors of the untrained arbitrary pixel points on the image space. The error convergence of the trained network with respect to the network control parameters were also presented. The compensated image through the network was then post processed using a simple DDA(Digital Differential Analyzer) to avoid the pixel disconnectivity. The compensation effect was verified using known sized geometric primitives. A way to extract directly a real scaled geometric quantity of the object from the 8-directional chain coding was also devised and coded. Since the developed calibration algorithm does not require any knowledge of modeling system elements and estimating parameters, it can be applied simply to any image processing system. Furthermore, it efficiently enhances the measurement accuracy and allows the arbitrary sizing and locating of the measuring window. The applied and developed algorithms were coded as a menu driven way using MS-C language Ver. 6.0, PC VISION PLUS library functions, and VGA graphic functions.

• The Journal of the Convergence on Culture Technology
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• v.6 no.4
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• pp.767-776
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• 2020

GcGAN is a deep learning model to translate styles between images under geometric consistency constraint. However, GcGAN has a disadvantage that it does not properly maintain detailed content of an image, since it preserves the content of the image through limited geometric transformation such as rotation or flip. Therefore, in this study, we propose a new image-to-image translation method, MSGcGAN(Multi-Scale GcGAN), which improves this disadvantage. MSGcGAN, an extended model of GcGAN, performs style translation between images in a direction to reduce semantic distortion of images and maintain detailed content by learning multi-scale images simultaneously and extracting scale-invariant features. The experimental results showed that MSGcGAN was better than GcGAN in both quantitative and qualitative aspects, and it translated the style more naturally while maintaining the overall content of the image.

• Journal of Broadcast Engineering
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• v.23 no.2
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• pp.227-234
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• 2018

Recently, stitching techniques are used for obtaining wide FOV, e.g., panorama contents, from normal cameras. Despite many proposed algorithms, the no objective quality evaluation method is developed, so the comparison of algorithms are performed only in subjective way. The paper proposes a 'Delaunay-triangulation based objective assessment method' for evaluating the geometric and photometric distortions of stitched or warped images. The reference and target images are segmented by Delaunay-triangulation based on matched points between two images, the average Euclidian distance is used for geometric distortion measure, and the average or histogram of PSNR for photometric measure. We shows preliminary results with several test images and stitching methods for demonstrate the benefits and application.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.2 s.302
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• pp.69-80
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• 2005

In these days, the technology development of the imaging/optic industry and the digital broadcasting replace the classic CRT with the new display devices that is getting slimmer and larger. Especially, when the general TV signal is applied directly to the wide gamut display using LED or laser, which can display higher chromatic colors that can't be reproduced on CRT, the color distortion occurs and it causes serious problems. Thus, in this paper the gamut mapping is studied, which gets rids of the color distortion and utilizes the wider color gamut than that of the CRT sufficiently. In the gamut mapping the general mapping concept is the increasement of the chroma on the same hue plane but it causes the over chromatic enhancement. So, the vector mapping, which increases the lightness md the chroma at the same time, is proposed to prevent the side effect. In the vector mapping the chromaticity is maintained constantly, hence the image can be seen more natural than that of the chroma mapping. By using the gamut fitting, it is compensated that the tone disappearance or the contour effect that is arose from the geometric properties of the input and the output color gamut. These gamut mapping and gamut fitting can prevent the color distortion and reproduce the natural image on the wide gamut displays.

• Journal of Korean Neurosurgical Society
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• v.62 no.4
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• pp.476-486
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• 2019

Objective : The functional information of $^{11}C$-methionine positron emission tomography (MET-PET) images can be applied for Gamma knife radiosurgery (GKR) and its image quality may affect defining the tumor. This study conducted the phantom-based evaluation for geometric accuracy and functional characteristic of diagnostic MET-PET image co-registered with stereotactic image in Leksell $GammaPlan^{(R)}$ (LGP) and also investigated clinical application of these images in metastatic brain tumors. Methods : Two types of cylindrical acrylic phantoms fabricated in-house were used for this study : the phantom with an array-shaped axial rod insert and the phantom with different sized tube indicators. The phantoms were mounted on the stereotactic frame and scanned using computed tomography (CT), magnetic resonance imaging (MRI), and PET system. Three-dimensional coordinate values on co-registered MET-PET images were compared with those on stereotactic CT image in LGP. MET uptake values of different sized indicators inside phantom were evaluated. We also evaluated the CT and MRI co-registered stereotactic MET-PET images with MR-enhancing volume and PET-metabolic tumor volume (MTV) in 14 metastatic brain tumors. Results : Imaging distortion of MET-PET was maintained stable at less than approximately 3% on mean value. There was no statistical difference in the geometric accuracy according to co-registered reference stereotactic images. In functional characteristic study for MET-PET image, the indicator on the lateral side of the phantom exhibited higher uptake than that on the medial side. This effect decreased as the size of the object increased. In 14 metastatic tumors, the median matching percentage between MR-enhancing volume and PET-MTV was 36.8% on PET/MR fusion images and 39.9% on PET/CT fusion images. Conclusion : The geometric accuracy of the diagnostic MET-PET co-registered with stereotactic MR in LGP is acceptable on phantom-based study. However, the MET-PET images could the limitations in providing exact stereotactic information in clinical study.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.31 no.6_2
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• pp.593-599
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• 2013

China's Mapping Satellite-1, developed by the China Aerospace Science and Technology Corporation (CASC), was launched in three years ago. The data from Mapping Satellite-1 are able to use for efficient surveying and geometric mapping application field. In this paper, we fuse the panchromatic and multispectral images of Changchun area, which are obtained from the Mapping Satellite-1, the one that is the Chinese first transmission-type three-dimensional mapping satellite. The four traditional image fusion methods, which are HPF, Mod.IHS, Panshar and wavelet transform, were used to approach for effectively fusing Mapping Satellite-1 remote sensing data. Subsequently we assess the results with some commonly used methods, which are known a subjective qualitative evaluation and quantitative statistical analysis approach. Consequently, we found that the wavelet transform remote sensing image fusion is the optimal in the degree of distortion, the ability of performance of details and image information availability among four methods. To further understand the optimal methods to fuse Mapping Satellite-1 images, an additional study is necessary.

• The Journal of the Korea Contents Association
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• v.12 no.10
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• pp.63-71
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• 2012

Depth understanding is important for stereoscopic and various methods including space design and cognitive science should be taken account in contents production. Among them, human scientific engineering such as human factor needs to be touched. More specifically, when the stereoscopic designer determines a binocular disparity, the viewpoint of the camera has to be matched with that of the audience. In this process, the structural problem by the distortion due to the dichoptic error is happened, Therefore, 3D sweetening process based on geometric re-analysis and human scientific engineering to minimize the visual fatigue is significant. This paper analyzes the inconsistency problems of the viewpoint in stereoscopic images, and we produce the stereoscopic image contents based on human factors.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.260-262
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• 2003

New Image registration techniques are developed for determining geometric distortions between two images of the same scene. First, the properties of the Fourier transform of a two dimensional function under the affine transformation are given. As a result, techniques for the estimation of the coefficients of the distortion model using the spectral frequency information are developed. Image registration can be achieved by applying the fast Fourier transform (FFT) technique for cross correlation of misregistered imagery to determine spatial distances. The correlation results may be rather broad, making detection of the peak difficult, what can be suppressed by enhancing cross-correlation technique. Yield greatly improves the delectability and high precision of image misregistration.

• Proceedings of the Korea Multimedia Society Conference
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• 2002.05d
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• pp.901-906
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• 2002

This paper is a research about method, that is used in Rapid Prototyping system, that inserts and extracts watermark in STL(standard transform language) that has a 3D geometrical model. The proposed algorithm inserts watermark in the vertex domain of STL facet without the distortion of 3D model. If we make use of a established algorithm for watermarking of STL, a watermark inserted to 3D model can be removed by simple attack that change order of facet. The proposed algorithm has robustness about these attack. Experiment results verify that the proposed algorithm, to encode and decode watermark in STL 3D geometrical model, doesn't distort a 3D model at all. And it shows that the proposed algorithm is available.