• Journal of The Korean Astronomical Society
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• v.40 no.3
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• pp.67-82
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• 2007

The basic building block of solar filaments/prominences is thin threads of cool plasma. We have studied the spectral properties of velocity threads, clusters of thinner density threads moving together, by analyzing a sequence of $H{\alpha}$ images of a quiescent filament. The images were taken at Big Bear Solar Observatory with the Lyot filter being successively tuned to wavelengths of -0.6, -0.3, 0.0, +0.3, and +0.6 ${\AA}$ from the centerline. The spectra of contrast constructed from the image data at each spatial point were analyzed using cloud models with a single velocity component, or three velocity components. As a result, we have identified a couple of velocity threads that are characterized by a narrow Doppler width($\Delta\lambda_D=0.27{\AA}$), a moderate value of optical thickness at the $H{\alpha}$ absorption peak($\tau_0=0.3$), and a spatial width(FWHM) of about 1". It has also been inferred that there exist 4-6 velocity threads along the line of sight at each spatial resolution element inside the filament. In about half of the threads, matter moves fast with a line-of-sight speed of $15{\pm}3km\;s^{-1}$, but in the other half it is either at rest or slowly moving with a line-of-sight velocity of $0{\pm}3km\;s^{-1}$. It is found that a statistical balance approximately holds between the numbers of blue-shifted threads and red-shifted threads, and any imbalance between the two numbers is responsible for the non-zero line-of-sight velocity determined using a single-component model fit. Our results support the existence not only of high speed counter-streaming flows, but also of a significant amount of cool matter either being at rest or moving slowly inside the filament.

• Journal of the Korean Wood Science and Technology
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• v.38 no.6
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• pp.532-540
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• 2010

The strength properties of wooden model retaining wall made of pitch pine (Pinus rigida Miller) was evaluated. Three different types of wooden model retaining wall were made of the 11cm square timber treated with CUAZ-2 (Copper Azole). The retaining wall was made into the 4 layers of crossbar and the 3 layers of vertical-bar, of which the size was 86 cm high, 200 cm long and 96 cm wide. Type I was control and in Type II 20 cm vertical-bars and 93 cm vertical-bars were arranged alternately to decrease wood usage. TypeIII was similar to TypeII except that the connection between crossbars was reinforced with the wooden armature. In each type, the strength properties of retaining wall were investigated by horizontal loading test and the deformation of structure by image processing (AICON 3D DPA-PRO system). In horizontal loading test of Type I, Type II and Type III was 63.17, 57.80, and 60.97 kN/m, respectively. The deformation of the top layer in Type II was 1.5 times larger than in Type I and Type III. Consequently, the economic efficiency and strength performance were better in Type III than in Type I and Type II.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.1
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• pp.47-54
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• 2021

Calculation of quantity at construction sites is a factor that has a great influence on construction costs, and it is important to calculate accurate values. In this study, topographic model was created by using drone photogrammetry and drone LiDAR to estimate earthwork volume. ortho image and DSM (Digital Surface Model) were constructed for the study area by drone photogrammetry, and DEM (Digital Elevation Model) of the target area was established using drone LiDAR. And through accuracy evaluation, accuracy of each method are 0.034m, 0.35m in horizontal direction, 0.054m, 0.25m in vertical direction. Through the research, the usability of drone photogrammetry and drone LiDAR for constructing geospatial information was presented. As a result of calculating the volume of the study site, the UAV photogrammetry showed a difference of 1528.1㎥ from the GNSS (Global Navigation Satellite System) survey performance, and the 3D Laser Scanner showed difference of 160.28㎥. The difference in the volume of earthwork is due to the difference in the topographic model, and the efficiency of volume calculation by drone LiDAR could be suggested. In the future, if additional research is conducted using GNSS surveying and drone LiDAR to establish topographic model in the forest area and evaluate its usability, the efficiency of terrain model construction using drone LiDAR can be suggested.

• Journal of Broadcast Engineering
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• v.16 no.2
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• pp.216-225
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• 2011

Following the proliferation of three-dimensional video contents and displays, many terrestrial broadcasting companies have been preparing for stereoscopic 3DTV service. In terrestrial stereoscopic broadcast, it is a difficult task to code and transmit two video sequences while sustaining as high quality as 2DTV broadcast due to the limited bandwidth defined by the existing digital TV standards such as ATSC. Thus, a terrestrial 3DTV broadcasting with a heterogeneous video codec system, where the left image and right images are based on MPEG-2 and H.264/AVC, respectively, is considered in order to achieve both high quality broadcasting service and compatibility for the existing 2DTV viewers. Without significant change in the current terrestrial broadcasting systems, we propose a joint rate control scheme for stereoscopic 3DTV service based on the heterogeneous dual codec systems. The proposed joint rate control scheme applies to the MPEG-2 encoder a quadratic rate-quantization model which is adopted in the H.264/AVC. Then the controller is designed for the sum of the left and right bitstreams to meet the bandwidth requirement of broadcasting standards while the sum of image distortions is minimized by adjusting quantization parameter obtained from the proposed optimization scheme. Besides, we consider a condition on maintaining quality difference between the left and right images around a desired level in the optimization in order to mitigate negative effects on human visual system. Experimental results demonstrate that the proposed bit rate control scheme outperforms the rate control method where each video coding standard uses its own bit rate control algorithm independently in terms of the increase in PSNR by 2.02%, the decrease in the average absolute quality difference by 77.6% and the reduction in the variance of the quality difference by 74.38%.

• Korean Journal of Remote Sensing
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• v.37 no.3
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• pp.503-514
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• 2021

Rice production with adequate level of area is important for decision making of rice supply and demand policy. It is essential to grasp rice cultivation areas in advance for estimating rice production of the year. This study was carried out to classify paddy rice cultivation in Gimje-si using sentinel-1 SAR (synthetic aperture radar) and UAV imagery in early July. Time-series Sentinel-1A and 1B images acquired from early May to early July were processed to convert into sigma naught (dB) images using SNAP (SeNtinel application platform, Version 8.0) toolbox provided by European Space Agency. Farm map and parcel map, which are spatial data of vector polygon, were used to stratify paddy field population for classifying rice paddy cultivation. To distinguish paddy rice from other crops grown in the paddy fields, we used the decision tree method using threshold levels and random forest model. Random forest model, trained by mainly rice cultivation area and rice and soybean cultivation area in UAV image area, showed the best performance as overall accuracy 89.9%, Kappa coefficient 0.774. Through this, we were able to confirm the possibility of early estimation of rice cultivation area in Gimje-si using UAV image.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.36 no.2
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• pp.43-50
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• 2018

The camera is a key element in image-based three-dimensional positioning, and camera calibration, which properly determines the internal characteristics of such a camera, is a necessary process that must be preceded in order to determine the three-dimensional coordinates of the object. In this study, a new methodology was proposed to determine interior orientation parameters of a camera semi-automatically without being influenced by size and shape of checkerboard for camera calibration. The proposed method consists of exterior orientation parameters estimation using quaternion, recognition of calibration target, and interior orientation parameter determination through bundle block adjustment. After determining the interior orientation parameters using the chessboard calibration target, the three-dimensional position of the small 3D model was determined. In addition, the horizontal and vertical position errors were about ${\pm}0.006m$ and ${\pm}0.007m$, respectively, through the accuracy evaluation using the checkpoints.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.2
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• pp.149-155
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• 2020

The Korea Highway Traffic Authority provides statistics that analyze the causes of traffic accidents that occurred since 2015 using the Traffic Accident Analysis System (TAAS). it was reported Through TAAS that the driver's forward carelessness was the main cause of traffic accidents in 2018. As statistics on the cause of traffic accidents, 51.2 percent used mobile phones and watched DMB while driving, 14 percent did not secure safe distance, and 3.6 percent violated their duty to protect pedestrians, representing a total of 68.8 percent. In this paper, we propose a system that has improved the advanced driver assistance system ADAS (Advanced Driver Assistance Systems) by utilizing CNN (Convolutional Neural Network) among the algorithms of Deep Learning. The proposed system learns a model that classifies the movement of the driver's face and eyes using Conv2D techniques which are mainly used for Image processing, while recognizing and detecting objects around the vehicle with cameras attached to the front of the vehicle to recognize the driving environment. Then, using the learned visual steering model and driving environment data, the hazard is classified and detected in three stages, depending on the driver's view and driving environment to assist the driver with the forward and blind spots.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.37 no.1
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• pp.1-15
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• 2000

To reconstruct 3- D shape, It is a common strategy to acquire multiple range Images from different viewpoints and integrate them into a common coordinates In this paper, we particularly focus on the registration and integration processes for combining all range Images into one surface model. For the registration, we propose the 2-step registration algorithm, which consists of 2 steps the rough registration step using all data points and the fine registration step using the high-curved data points For the integration, we propose a new algorithm, referred to as ‘multi-registration’ technique, to alleviate the error accumulation problem, which occurs during applying the pair-wise registration to each range image sequentially, in order to transform them into a common reference frame Intensive experiments are performed on the various real range data In experiments, all range images were registered within 1 minutes on Pentium 150MHz PC The results show that the proposed algorithms registrate and integrate multiple range Images within a tolerable error bound in a reasonable computation time, and the total error between all range Images are equalized with our proposed algorithms.

• Proceedings of the KSRS Conference
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• 1998.09a
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• pp.236-241
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• 1998

The NOAA AVHRR remote sense SST data, collected by the National Fisheries Research and Development Institute (NFRDI), are analyzed in order to understand the spatial and temporal distributions of SST in the seas adjacent to Korea. Our study is based on 10-day SST images during last 7 years (1991-1997). For a time series analysis of multiple 557 images, all of images must be aligned exactly at the same position by adjusting the scales and positions of each SST image. We devised an algorithm which yields automatic detections of cloud pixels from multiple SST images. The cloud detection algorithm is based on a physical constraint that SST anomalies in the ocean do not exceed certain limits (we used $\pm$ 3$^{\circ}C$ as a criterion of SST anomalies). The remote sense SST data are tuned by comparing remote sense data with observed SST at coastal stations. Seasonal variations of SST are studied by harmonic fit of SST normals at each pixel. The SST anomalies are studied by statistical method. We found that the SST anomalies are rather persistent with time scales between 1 and 2 months. Utilizing the persistency of SST anomalies, we devised an algorithm for a prediction of future SST Model fit of SST anomalies to the Markov process model yields that autoregression coefficients of SST anomalies during a time elapse of 10 days are between 0.5 and 0.7. We plan to improve our algorithms of automatic cloud pixel detection and prediction of future SST. Our algorithm is expected to be incorporated to the operational real time service of SST around Korea.

• Journal of the Korea Computer Graphics Society
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• v.21 no.3
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• pp.55-61
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• 2015

In this paper, we introduce a method to synthesize realistic make-up effects on input images efficiently. In particular, we focus on shading on the make-up effects due to the lighting and face curvature. By doing this, we can synthesize a wider range of effects realistically than the previous methods. To do this, the information about lighting information together with the normal vectors on all pixels over the face region in the input image. Since the previous methods that compute lighting information and normal vectors require relatively heavy computation cost, we introduce an approach to approximate lighting information using cascade pose regression process and normal vectors by transforming, rendering, and warping a standard 3D face model. The proposed method consumes much less computation time than the previous methods. In our experiment, we show the proposed approximation technique can produce naturally looking virtual make-up effects.