• Journal of Radiation Protection and Research
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• v.30 no.4
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• pp.237-245
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• 2005

The distribution of radionuclides in soil and plants were calculated, assuming an accidental release of radionuclides from Yeonggwang Nuclear Power Plant. The results which show the concentration change with time and regions were displayed by GIS. GIS Included the commercial program, ArcView(ESRI), and a basic digital map of 1:5000 scale for 30km by 30km area around Yeonggwang Nuclear Power Plant. The target material was $^{137}Cs$ in soil around Yeonggwang area. Given denosited $^{137}Cs$ concentrations, ECOREA-II code computed the $^{137}Cs$ concentration of the soil and the plant in the area divided by 16 azimuth, 480 unit cells in total in which the concentrations also varied with time. The results were introduced into the attributed data of previously designed polygon cells in ArcView. In order to display the concentration change with time by monotonic color, the RGB value for ArcView color lamp was controlled. This display is useful for the public to understand the concentration change of radionuclide around Yeonggwang area definitely.

• Korean Journal of Plant Resources
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• v.29 no.4
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• pp.363-375
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• 2016

Potentilla kleiniana is a perennial herb beloning to Rosaceae family. Herein we investigated the effect of light intensity, light quality and chemical elicitor on plant growth and the accumulation of bioactive compounds in P. kleiniana. After 60 days of cultivation under different shading level [0% (200 μmol·m⁻²·s⁻¹), 35% (95 μmol·m⁻²·s⁻¹), 55% (65 μmol·m⁻²·s⁻¹), 75% (40 μmol·m⁻²·s⁻¹)] in the greenhouse, chlorophyll and carotenoid content were the highest under 35% treatment, however, plant height, leaf number and biomass were the highest under non-shading. As a result of cultivation among strong light condition as a control, florescence and three mixture light sources [red:white:blue (RWB) = 8:1:1, red:blue (RB) = 8:2, red:green:blue (RGB) = 8:1:1] as treatments in plant growth chamber (25 ± 2℃, 185 ± 3 μmol·m⁻²·s⁻¹), growth, biomass, chlorophyll content low difference between total phenolic compouds and flavonoid content were higher under RWB treatment. DPPH radical elimination ability was the highest under all treatments especially florescence and RGB treatment except control. As a result of treating chemical elicitor [salicylic acid (SA), methyl jasmonate (MeJA)] concentration (0, 50, 100, 200 μM) respectively, plant height, petiole diameter and biomass were higher under non-treatment, MeJA 50 μM. It was investigated that fresh weight and dry weight under MeJA 50 μM treatment were especially a little high. Total phenolic compounds and flavonoid content of SA 50 μM treatment was the highest but DPPH radical elimination ability was significantly the highest under MeJA 200 μM (88.65%) and MeJA 50 μM (87.84%) treatment. Thus, this study suggested that we determined optimal shading and light quality in the greenhouse and plant growth chamber also confirmed bioactive compound content, antioxidant ratio increase according to different chemical elicitation concentration.

• Journal of the Korean Institute of Gas
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• v.21 no.5
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• pp.1-8
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• 2017

Currently gas safety management in the industrial field has been done by LDAR as contact method or methane leak detector as non-contact method. But LDAR method requires a lot of man-power and methane leak detector have the limitation of methane only. Therefore the Research on the OGI(optical gas image) has big attention by industry. This research was undertaken to see the effect of background temperature difference of gas cloud on the clarity of OGI. The background temperature control panel was constructed to cool down the background temperature. OGI was taken at the various methane gas ejection rate and the designed temperature difference. The experimental results showed that the OGI(when the temperature difference is $-6^{\circ}C$) is more clear thane the OGI(when the temperature difference is zero). To quantify the clarity difference, MATLAB's RGB analysis method was employed. The RGB value of the OGI at ${\Delta}T-6^{\circ}C$ was 20% lower than the OGI at ${\Delta}T0^{\circ}C$. The clarity difference by T difference can be explained by the total radiation law. When the background temperature of the gas is lower than the air temperature, the radiation energy coming into the OGI lens is increasing. As the energy is increasing, the OGI image becomes clear.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.49 no.4
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• pp.40-48
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• 2012

This paper models the hue shift phenomenon and proposes a hue correction method to give perceptual matching between projector with and without additional white channel. To quantify the hue shift phenomenon for whole hue angle, 24 color patches with the same lightness are frist created along equally-spaced hue angle, and these are displayed one by one both displays with different luminance levels. Next, each hue value of the patches appeared on the projector with additional white channel is adjusted by observers until the hue values of patches on both displays appear the same visually. After obtaining the hue shift values from the color matching experiment, these values are piecewise fit into six polynomial functions, which approximately determine shifted hue amounts for an arbitrary hue values of each pixel in projector with additional white channel and are utilized to correct them. Actually, an input RGB image is converted to CIELAB LCH color space to get hue values of each pixel and this hue value is shifted as much as the amount calculated by the functions of hue shift model for correction. Finally, corrected image is inversely converted to an output RGB image. For an evaluation, the matching experiment with several test images and the z-score comparisons were performed.

• Journal of IKEEE
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• v.18 no.4
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• pp.485-494
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• 2014

Traffic Sign Recognition(TSR) is an important element in an Advanced Driver Assistance System(ADAS). However, many studies related to TSR approaches only in normal daytime environment because a sign's unique color doesn't appear in poor environment such as night time, snow, rain or fog. In this paper, we propose a new TSR algorithm based on machine learning for daytime as well as poor environment. In poor environment, traditional methods which use RGB color region doesn't show good performance. So we extracted sign characteristics using HoG extraction, and detected signs using a Support Vector Machine(SVM). The detected sign is recognized by a decision tree based on 25 reference points in a Normalized RGB system. The detection rate of the proposed system is 96.4% and the recognition rate is 94% when applied in poor environment. The testing was performed on an Intel i5 processor at 3.4 GHz using Full HD resolution images. As a result, the proposed algorithm shows that machine learning based detection and recognition methods can efficiently be used for TSR algorithm even in poor driving environment.

• Journal of Korea Multimedia Society
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• v.13 no.5
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• pp.641-650
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• 2010

Color image sensors (CIS) output color images through image sensors and image signal processing. Image sensors that convert light to electrical signal are divided into CMOS image sensor and CCD image sensor according to transferring method of signal charge. In general, a CIS has RGB output signals from tri-stimulus XYZ of the scene through image signal processing. This paper presents an adaptive colorimetric analysis method to obtain chromaticity and luminance using CIS under various environments. An image sensor for the use of colorimeter is characterized based on the CIE standard colorimetric observer. We use the method of least squares to derive a colorimetric characterization matrix between camera RGB output signals and CIE XYZ tristimulus values. We first survey the camera characterization in the standard environment then derive a SGL(shutter-gain-level) function which is relationship between luminance and auto exposure (AE) characteristic of CIS, and read the status of an AWB(auto white balance) function. Then we can apply CIS to measure luminance and chromaticity from camera outputs and AE resister values without any preprocessing. Camera RGB outputs, register values, and camera photoelectric characteristic are used to analyze the colorimetric results for real scenes such as chromaticity and luminance. Experimental results show that the proposed method is valid in the measuring performance. The proposed method can apply to various fields like surveillant systems of the display or security systems.

• Proceedings of the KSMRM Conference
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• 2002.11a
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• pp.133-133
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• 2002

Purpose： The purpose of paper is to implement software to visualize brain fiber tract using a 24-bit color coding scheme and to test its feasibility. Materials and Methods： MR imaging was performed on GE 1.5 T Signa scanner. For diffusion tensor image, we used a single shot spin-echo EPI sequence with 7 non-colinear pulsed-field gradient directions： (x, y, z)：(1,1,0),(-1,1,0),(1,0,1),(-1,0,1),(0,1,1),(0,1,-1) and without diffusion gradient. B-factor was 500 sec/$\textrm{mm}^2$. Acquisition parameters are as follows： TUTE=10000ms/99ms, FOV=240mm, matrix=128${\times}$128, slice thickness/gap=6mm/0mm, total slice number=30. Subjects consisted of 10 normal young volunteers (age：21∼26 yrs, 5 men, 5 women). All DTI images were smoothed with Gaussian kernel with the FWHM of 2 pixels. Color coding schemes for visualization of directional information was as follows. HSV(Hue, Saturation, Value) color system is appropriate for assigning RGB(Red, Green, and Blue) value for every different directions because of its volumetric directional expression. Each of HSV are assigned due to (r,$\theta$,${\Phi}$) in spherical coordinate. HSV calculated by this way can be transformed into RGB color system by general HSV to RGB conversion formula. Symmetry schemes： It is natural to code the antipodal direction to be same color(antipodal symmetry). So even with no symmetry scheme, the antipodal symmetry must be included. With no symmetry scheme, we can assign every different colors for every different orientation.(H =${\Phi}$, S=2$\theta$/$\pi$, V=λw, where λw is anisotropy). But that may assign very discontinuous color even between adjacent yokels. On the other hand, Full symmetry or absolute value scheme includes symmetry for 180$^{\circ}$ rotation about xy-plane of color coordinate (rotational symmetry) and for both hemisphere (mirror symmetry). In absolute value scheme, each of RGB value can be expressed as follows. R=λw｜Vx｜, G=λw｜Vy｜, B=λw｜Vz｜, where (Vx, Vy, Vz) is eigenvector corresponding to the largest eigenvalue of diffusion tensor. With applying full symmetry or absolute value scheme, we can get more continuous color coding at the expense of coding same color for symmetric direction. For better visualization of fiber tract directions, Gamma and brightness correction had done. All of these implementations were done on the IDL 5.4 platform.

• Journal of Korea Multimedia Society
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• v.10 no.2
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• pp.209-217
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• 2007

This paper proposed to a detection scheme of weather information that is a part of CCTV Images Weather Detection System using CCTV images and Temperature, Humidity. The previous Partial Weather Detection System uses how to acquire weather information using images on the Road. In the system the contrast and RGB Values using clear images are gained. This information is distributed a input images to cloud, rain, snow and fog images. That is, this information is compared the snow and the fog images for acquisition more correctness information us ing difference images and binary images. Currently, We use to environment sense system, but we suggest a new Weather Detection Algorithm to detect weather information using CCTV images. Our algorithm is designed simply and systematically to detect and separate special characteristics of images from CCTV images. and using temperature & humidity in formation. This algorithm, there is more complex to implement than how to use DB with high overhead of time and space in the previous system. But our algorithm can be implement with low cost' and can be use the system in real work right away. Also, our algorithm can detect the exact information of weather with adding in formation including temperature, humidity, date, and time. At last, this paper s how the usefulness of our algorithm.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.4
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• pp.211-221
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• 2021

The Rabbit grass(Trifolium Repens, call it 'Clover') is a representative harmful plant of lawn, and it starts growing earlier than lawn, forming a water pipe on top of the lawn and hindering the photosynthesis and growth of the lawn. As a result, in competition between lawn and clover, clover territory spreads, but lawn is damaged and dried up. Damage to the affected lawn area will accelerate during the rainy season as well as during the plant's rear stage, spreading the area where soil is exposed. Therefore, the restoration of damaged lawn is causing psychological stress and a lot of economic burden. The purpose of this study is to distinguish clover which is a representative harmful plant on lawn, to identify the distribution of damaged areas due to the spread of clover, and to review of changes in vegetation before and after the eradication of clover. For this purpose, a time series analysis of three vegetation indices calculated based on images of convergence Drone with RGB(Red Green Blue) and BG-NIR(Near Infra Red)sensors was reviewed to identify the separation between lawn and clover for selective eradication, and the distribution of damaged lawn for recovery plan. In particular, examined timeseries changes in the ecology of clover before and after the weed-whacking by manual and brush cutter. And also, the method of distinguishing lawn from clover was explored during the mid-year period of growth of the two plants. This study shows that the time series analysis of the MGRVI(Modified Green-Red Vegetation Index), NDVI(Normalized Difference Vegetation Index), and MSAVI(Modified Soil Adjusted Vegetation Index) indices of drone-based RGB and BG-NIR images according to the growth characteristics between lawn and clover can confirm the availability of change trends after lawn damage and clover eradication.

• The Journal of the Korea Contents Association
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• v.22 no.3
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• pp.71-80
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• 2022

In the past, fish diseases were bacterial in aqua farms, but in recent years, the frequency of fish diseases has increased as they have become viral and mixed. Viral diseases in an enclosed space called a aqua farm have a high spread rate, so it is very likely to lead to mass death. Fast identification of fish diseases is important to prevent group death. However, diagnosis of fish diseases requires a high level of expertise and it is difficult to visually check the condition of fish every time. In order to prevent the spread of the disease, an automatic identification system of diseases or fish is needed. In this paper, in order to improve the performance of the disease identification system of Paralichthys olivaceus based on deep learning, the existing pre-processing method is compared and tested. Target diseases were selected from three most frequent diseases such as Scutica, Vibrio, and Lymphocystis in Paralichthys olivaceus. The RGB, HLS, HSV, LAB, LUV, XYZ, and YCRCV were used as image pre-processing methods. As a result of the experiment, HLS was able to get the best results than using general RGB. It is expected that the fish disease identification system can be advanced by improving the recognition rate of diseases in a simple way.