• Korean Journal of Remote Sensing
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• v.31 no.2
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• pp.171-182
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• 2015

We propose a camera system to acquire indoor stereo omni-directional images and its calibration method. These images can be utilized for indoor precise mapping and sophisticated imagebased services. The proposed system is configured with a rotating stereo line camera system, providing stereo omni-directional images appropriate to stable stereoscopy and precise derivation of object point coordinates. Based on the projection model, we derive a mathematical model for the system calibration. After performing the system calibration, we can estimate object points with an accuracy of less than ${\pm}16cm$ in indoor space. The proposed system and calibration method will be applied to indoor precise 3D modeling.

• Journal of Korea Multimedia Society
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• v.6 no.7
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• pp.1286-1301
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• 2003

This paper introduces segmentation based environment modeling method and integration method using multiple environment map for constructing the realtime image-based panoramic navigation system. The segmentation-based environment modeling method is easy to implement on the environment map and can be used for environment modeling by extracting the depth value by the segmentation of the environment map. However, an environment model that is constructed using a single environment map has the problem of a blurring effect caused by the fixed resolution, and the stretching effect of the 3D model caused when information that does not exist on the environment map occurs due to the occlusion. In this paper, we suggest environment models integration method using multiple environment map to resolve the above problem. This method can express parallax effect and expand the environment model to express wide range of environment. The segmentation-based environment modeling method using multiple environment map can build a detail model with optimal resolution.

• Korean Journal of Soil Science and Fertilizer
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• v.43 no.4
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• pp.415-423
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• 2010

Pore network models are useful tools to investigate soil pore geometry. These models provide quantitative information of pore geometry from 3D images. This study presents a pore network model to quantify pore structure and hydraulic characteristics. The objectives of this work were to apply the pore network model to characterize pore structure from large images to quantify pore structure, calculate water retention and hydraulic conductivity properties from a three dimensional soil image, and to combine measured hydraulic properties from experiments with calculated hydraulic properties from image. Soil samples were taken from a site located at the Baltimore science center, which is located inside of the city. Undisturbed columns were taken from the site and scanned with a computer tomographer at resolutions of 22 ${\mu}m$. Pore networks were extracted by medial-axis transformation and were used to measure pore geometry from one of the scanned samples. Water retention and unsaturated hydraulic conductivity values were calculated from the soil image. Properties of soil bulk density, water retention and unsaturated hydraulic conductivity were measured from three replicates of scanned soil samples. 3D image analysis provided accurate detailed pore properties such as individual pore volumes, pore length, and tortuosity of all pores. These data made possible to calculate accurate estimations of water retention and hydraulic conductivity. Combination of the calculated and measured hydraulic properties gave more accurate information on pore sizes over wider range than measured or calculated data alone. We could conclude that the hydraulic property computed from soil images and laboratory measurements can describe a full structure of intra- and inter-aggregate pores in soil.

• The korean journal of orthodontics
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• v.36 no.1 s.114
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• pp.14-29
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• 2006

Developments in computer technology have made possible the 3-dimensional (3-D) evaluation of hard and soft tissues in orthodontic diagnosis, treatment planning and post-treatment results. In this study, Korean adults with normal occlusion (male 30, female 30) were scanned by a 3-D laser scanner, then 3-D facial images formed by the Rapidform 2004 program (Inus Technology Inc., Seoul, Korea.). Reference planes in the facial soft tissue 3-D images were established and a 3-D coordinate system (X axis-left/right, Y axis-superior/inferior, Z axis-anterior/posterior) was established by using the soft tissue nasion as the zero point. Twenty-nine measurement points were established on the 3-D image and 43 linear measurements, 8 angular measurements, 29 linear distance ratios were obtained. The results are as follows; there were significant differences between males and females in the nasofrontal angle $(male:\;142^{\circ},\;female:\;147^{\circ})$ and transverse nasal prominence $(male:\;112^{\circ},\;female:\;116^{\circ})$ (p<0.05). The transverse upper lip prominence was $107^{\circ}$ in males, $106^{\circ}$ in females and the transverse mandibular prominence was $76^{\circ}$ in both males and females. Li-Me' was 0.4 times the length of Go-Me'(mandibular body length) and the mouth height was also 0.4 times the width of the mouth width. The linear distance ratio from the coronal reference plane of FT, Zy, Pn, ULPm, Li, Me' was -1/-1/1/0.5/0.5/-0.6 respectively. The 3-D facial model of Korean adults with normal occlusion were be constructed using coordinate values and linear measurement values. These data may be used as a reference in 3-D diagnosis and treatment planning for malocclusion and dentofacial deformity patients and applied for 3-D analysis of facial soft tissue changes before and after orthodontic treatment and orthognathic surgery.

• Journal of Biomedical Engineering Research
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• v.39 no.3
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• pp.116-123
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• 2018

This study is a model experimental study using a phantom to propose an optimized brain CT scan protocol that can reduce the radiation dose of a patient and remain quality of image. We investigate the CT scan parameters of brain CT in clinical medical institutions and to measure the important parameters that determine the quality of CT images. We used 52 multislice spiral CT (SOMATOM Definition AS+, Siemens Healthcare, Germany). The scan parameters were tube voltage (kVp), tube current (mAs), scan time, slice thickness, pitch, and scan field of view (SFOV) directly related to the patient's exposure dose. The CT dose indicators were CTDIvol and DLP. The CT images were obtained while increasing the imaging conditions constantly from the phantom limit value (Q1) to the maximum value (Q4) for AAPM CT performance evaluation. And statistics analyzed with Pearson's correlation coefficients. The result of tube voltage that the increase in tube voltage proportionally increases the variation range of the CT number. And similar results were obtained in the qualitative evaluation of the CT image compared to the tube voltage of 120 kVp, which was applied clinically at 100 kVp. Also, the scan conditions were appropriate in the tube current range of 250 mAs to 350 mAs when the tube voltage was 100 kVp. Therefore, by applying the proposed brain CT scanning parameters can be reduced the radiation dose of the patient while maintaining quality of image.

• The Bulletin of The Korean Astronomical Society
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• v.37 no.2
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• pp.107.1-107.1
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• 2012

We present the results of far-ultraviolet (FUV) observations of comet C/2001 Q4 (NEAT) obtained with Far-ultraviolet Imaging Spectrograph (FIMS) on board the Korean microsatellite STSAT-1, which operated at an altitude of 700 km in a sun-synchronous orbit. FIMS is a dual-channel imaging spectrograph (S channel 900-1150 ${\AA}$, L channel 1350-1750 ${\AA}$, ${\lambda}/{\Delta}{\lambda}$ ~ 550) with large image fields of view (S: $4^{\circ}.0{\times}4^{\prime}.6$, L: $7^{\circ}.5{\times}4^{\prime}.3$, angular resolution 5'-10') optimized for the observation of diffuse emission of astrophysical radiation. Comet C/2001 Q4 (NEAT) was observed with a scanning survey mode when it was located around the perihelion between 8 and 15 May 2004. Several important emission lines were detected including S I (1425, 1474 ${\AA}$), C I (1561, 1657 ${\AA}$) and several emission lines of CO $A^1{\Pi}-X^1{\Sigma}^+$ system in the L channel. Production rates of the notable molecules, such as C I, S I and CO, were estimated from the photon fluxes of these spectral lines and compared with previous observations. We compare the flux and the production rates in the radius of $3{\times}10^5$ km with $20{\times}10^5$ km from the central coma. We obtained L-channel image which have map size $5^{\circ}{\times}5^{\circ}$ The image was constructed for the wavelength band of L-channel (1350 - 1710 ${\AA}$. We also present the radial profiles of S I, C I, CO obtained from the spectral images of the central coma. The radial profiles of $2{\times}10^6$ km region are compared with the Haser model.

• Journal of Intelligence and Information Systems
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• v.28 no.2
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• pp.263-278
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• 2022

With the recent advent of IoT technology, automatic pet feeders are being distributed so that owners can feed their companion animals while they are out. However, due to behaviors of pets, the method of measuring weight, which is important in automatic feeding, can be easily damaged and broken when using the scale. The 3D camera method has disadvantages due to its cost, and the 2D camera method has relatively poor accuracy when compared to 3D camera method. Hence, the purpose of this study is to propose a deep learning approach that can accurately estimate weight while simply using a 2D camera. For this, various convolutional neural networks were used, and among them, the ResNet101-based model showed the best performance: an average absolute error of 3.06 grams and an average absolute ratio error of 3.40%, which could be used commercially in terms of technical and financial viability. The result of this study can be useful for the practitioners to predict the weight of a standardized object such as feed only through an easy 2D image.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.26 no.3
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• pp.227-239
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• 2008

Processing LiDAR (Light Detection And Ranging) data obtained from ALS (Airborne Laser Scanning) systems mainly involves organization and segmentation of the data for 3D object modeling and mapping purposes. The ALS systems are viable and becoming more mature technology in various applications. ALS technology requires complex integration of optics, opto-mechanics and electronics in the multi-sensor components, Le. data captured from GPS, INS and laser scanner. In this study, digital image processing techniques mainly were implemented to gray level coded image of the LiDAR data for building extraction and superstructures segmentation. One of the advantages to use gray level image is easy to apply various existing digital image processing algorithms. Gridding and quantization of the raw LiDAR data into limited gray level might introduce smoothing effect and loss of the detail information. However, smoothed surface data that are more suitable for surface patch segmentation and modeling could be obtained by the quantization of the height values. The building boundaries were precisely extracted by the robust edge detection operator and regularized with shape constraints. As for segmentation of the roof structures, basically region growing based and gap filling segmentation methods were implemented. The results present that various image processing methods are applicable to extract buildings and to segment surface patches of the superstructures on the roofs. Finally, conceptual methodology for extracting characteristic information to reconstruct roof shapes was proposed. Statistical and geometric properties were utilized to segment and model superstructures. The simulation results show that segmentation of the roof surface patches and modeling were possible with the proposed method.

• Geophysics and Geophysical Exploration
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• v.20 no.1
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• pp.33-42
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• 2017

Recently, the grounded electrical-source airborne transient electromagnetic (GREATEM) system with high power source was introduced to achieve deeper investigation depth and to overcome high noise level. Although the GREATEM is a transient electromagnetic system using a long grounded wire as the transmitter, GREATEM data have been interpreted with 1D earth models because 2D or 3D modeling and inversion of vast airborne data are complicated and expensive to calculate. Generally, 1D inversion is subsequently applied to every survey point and combining 1D images together forms the stitched conductivity-depth image. However, the stitched models often result in abrupt variations in neighboring models. To overcome this problem, laterally constrained inversion (LCI) has been developed in inversion of ATEM data, which can yield layered sections with lateral smooth transitions. In this study, we analysed the GREATEM data through 1D numerical modeling for a curved grounded wire source. Furthermore, we developed a laterally constrained inversion scheme for continuous GREATEM data based on a layered earth model. All 1D data sets and models are inverted as one system, producing layered sections with lateral smooth transitions. Applying the developed LCI technique to the GREATEM data, it was confirmed that the laterally constrained inversion can provide laterally smooth model sections that reflect the layering of the survey area effectively.

• Journal of Korea Water Resources Association
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• v.56 no.3
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• pp.211-224
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• 2023

In this study, a soil moisture estimation was performed using the Water Cloud Model (WCM), a backscatter model that considers vegetation based on SAR (Synthetic Aperture Radar). Sentinel-1 SAR and Sentinel-2 MSI (Multi-Spectral Instrument) images of a 40 × 50 km² area including the Yongdam Dam watershed of the Geum River were collected for this study. As vegetation descriptor of WCM, Sentinel-1 based vegetation index RVI (Radar Vegetation Index), depolarization ratio (DR), and Sentinel-2 based NDVI (Normalized Difference Vegetation Index) were used, respectively. Forward modeling of WCM was performed by 3 groups, which were divided by the characteristics between backscattering coefficient and soil moisture. The clearer the linear relationship between soil moisture and the backscattering coefficient, the higher the simulation performance. To estimate the soil moisture, the simulated backscattering coefficient was inverted. The simulation performance was proportional to the forward modeling result. The WCM simulation error showed an increasing pattern from about -12dB based on the observed backscattering coefficient.