• Title/Summary/Keyword: gray value

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Analysis of Digital Images of Skin Reaction Induced By Ultraviolet Irradiation (자외선 조사에 의한 피부 반응의 디지털 영상분석)

  • Lee, Dong-Yeop;Doo, Yeong-Taek;Lee, Jeong-Woo
    • Journal of the Korean Academy of Clinical Electrophysiology
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    • v.8 no.2
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    • pp.39-43
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    • 2010
  • Purpose : The purpose of this study was to analyze skin reactions induced by ultraviolet irradiation using digital imagery. Methods : We recruited 15 women and ultraviolet irradiation was applied to their lumbar area. (The degree of inflammatory reaction was set on the basis of the third erythema dose. Image analysis was divided by Photoshop CS (8 bit RGB scale and gray scale). Then, images were processes using Image Pro Plus 4.5 program analyzing R, G, B, chromatic red value, luminance value and gray value. Results : As a result of analyzing changes in RGB scale, there were statistically significant differences in R, G, and chromatic red values. As a result of analyzing changes in gray scale, there were statistically significant differences in gray value. Analysis of changes in B and luminance values showed that there was no statistically significant difference. Conclusion : This study found that ultraviolet irradiation had influence on RGB and gray scale. These results suggest that changes to digital images on skin reaction by ultraviolet irradiation are related to erythema. In particular, these changes are related to R and gray values.

Determination of Background Gray-level for Accurate Measurement of Particles in using Image Processing Method (영상처리 기법을 이용한 입경 측정시 배경 명도가 측정 정밀도에 미치는 영향)

  • Koh, Kwang-Uoong;Lee, Sang-Yong
    • Transactions of the Korean Society of Mechanical Engineers B
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    • v.24 no.4
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    • pp.599-607
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    • 2000
  • In this study, experiments have been performed to examine the effects of background gray-level on the depth-of-field and on the in-focus criteria. The normalized value of contrast(VC) and the gradient indicator(GI) were used as the in-focus criteria for the small and the large size-ranges of particles, respectively. The slightly larger number of pixels were detected with the brighter background. The maximum of the normalized value of contrast(VCmax) is decreased with the brighter background and its deviation from that with the background gray-level of 160 turned out to be about $pm$15% when the background gray-level changes from 100 to 200. However, the maximum gradient indicator(GImax) changes with the background gray-level within only $pm$5%. The depth-of-field for the VC-applicable particle-size range is largely dependent on the background gray-level. On the other hand, the depth-of-field for the GI-applicable particle-size range changes only slightly with the background gray-level. To keep the normalized standard deviation of the particle size within 0.1, the background gray-level should be set 160$pm$20 for both the VC-applicable and GI-applicable ranges which cover the particle size between $10{\mu}m$ and $300{\mu}m$.

Segmentation and Volume Calculation through the Analysis of Blurred Gray Value from the Brain MRI (뇌의 MR 영상에서 번짐 현상의 명암 값 분석을 통한 백질과 회백질의 추출 및 체적 산출)

  • Sung, Yun-Chang;Yoo, Seung-Wha;Song, Chang-Jun;Park, Jong-Won
    • Journal of KIISE:Software and Applications
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    • v.27 no.8
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    • pp.815-826
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    • 2000
  • This study is for the segmentation and volume calculation of the white matter and gray matter from brain MRI. In general, the volume of white and gray matter is reduced by contraction of each components in the case of mental retardation which are Alzheimer's disease and Down's syndrome. As results, it is useful for diagnostic and early detection for various mental retardation through the tracing of variation for its volume from the brain MRI. But, until now, it was very difficult to calculate the partial volume of each components existing in some thickness, because MR image was represented by single gray value after scanning by MR scanner. Accordingly, new segmentation algorithm proposed in this paper is to calculate the partial volume of the white and gray matter existing in some thickness through the analysis of the blurred gray value, and is to determine the threshold for segmentation of white and gray matter, and is to calculate the volume of each segmented component. And finally, proposed algorithm was applied the models which was created manually, and then acquired results was compared with that of original model.

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A Study on Segmentation and Volume Calculation of the White Matter and Gray Matter for Brain Image Processing (뇌 영상처리를 위한 백질과 회백질의 추출 및 체적 산출에 관한 연구)

  • Kim, Shin-Hong
    • 전자공학회논문지 IE
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    • v.43 no.4
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    • pp.21-27
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    • 2006
  • This paper is for the segmentation and volume calculation of the white matter and gray matter from brain MRI. We segment white matter, gray matter and CSF from the Brain image in the normal and abnormal person, and calculate the volume of segmented tissue. In this paper, we present a new method of extracting white matter, gray matter and CSF and calculation its volume from MR images for brain. And we have developed the determining method of threshold that can extract white matter and gray matter from MR image for brain through the analysis of gray values represented by ratio of each component. We proposed the calculation method of volume for white matter and gray matter by using number of extracted pixels in each slice. This algorithm input CSF/Head volume ratio and age of patient and calculates discriminant value through discriminant expression, classifies normal and abnormal using calculated discriminant value. As a result, we could blow that white matter and gray matter volume decrease and CSF volume increase as we grow gold.

FPGA based Dynamic Thresholding Circuit

  • Cho, J.U.;Lee, S.H.;Jeon, J.W.;Kim, J.T.;Cho, J.D.;Lee, K.M.;Lee, J.H.;Byun, J.E.;Choi, J.C.
    • 제어로봇시스템학회:학술대회논문집
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    • 2004.08a
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    • pp.1235-1238
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    • 2004
  • Thresholding has been used to reduce the number of gray values in images. Typically, a single threshold value has been used, resulting in two gray level images. Image reduction of one single threshold value, however, may lose too much of the high-frequency edge information. Thus, dynamic thresholding that uses a different threshold for each pixel is preferred instead of using a single threshold value. Dynamic thresholding can preserve high frequency details as well as reduce the size of images. Since it takes long time to perform existing software dynamic thresholding in an embedded system, this paper proposes and implements a circuit by using a FPGA in order to perform a real-time dynamic thresholding,. The proposed circuit consists of two counters, and threshold look-up table, and control unit. The values of two counters determine each pixel position, the threshold look-up table converts each pixel value into other value, and the control unit generates necessary control signals. On arriving from a camera to the proposed circuit, each pixel is compared with its threshold value and is converted into other gray value. An image processing system by using the proposed circuit will be implemented and some experiments will be performed.

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Structural monitoring and maintenance by quantitative forecast model via gray models

  • C.C. Hung;T. Nguyen
    • Structural Monitoring and Maintenance
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    • v.10 no.2
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    • pp.175-190
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    • 2023
  • This article aims to quantitatively predict the snowmelt in extreme cold regions, considering a combination of grayscale and neural models. The traditional non-equidistant GM(1,1) prediction model is optimized by adjusting the time-distance weight matrix, optimizing the background value of the differential equation and optimizing the initial value of the model, and using the BP neural network for the first. The adjusted ice forecast model has an accuracy of 0.984 and posterior variance and the average forecast error value is 1.46%. Compared with the GM(1,1) and BP network models, the accuracy of the prediction results has been significantly improved, and the quantitative prediction of the ice sheet is more accurate. The monitoring and maintenance of the structure by quantitative prediction model by gray models was clearly demonstrated in the model.

Evaluation of Fungicides for Control of Gray Snow Mold Caused by Typhula incarnata on Cool Season Turfgrass (한지형 잔디의 설부소립균핵병 방제를 위한 살균제 평가)

  • Chang, Tae-Hyun;Lee, Seung-Jun
    • Asian Journal of Turfgrass Science
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    • v.26 no.2
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    • pp.102-109
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    • 2012
  • Commercial formulation of fungicides was studied in the golf course for evaluation against Typhula incarnata causal agents of gray snow mold. Efficacies of fungicides application, fungicide mixture, fungicides applied method (irrigation and spray) and fungicides applied time (early fall and late fall) were evaluated for their influence on the chemical control of gray snow mold of turfgrass during the winter season in Yongpyeong golf course, Korea. Unsprayed control has significantly more disease severity than three fungicides (azoxystrobin, propiconazole, and tebuconazole) were applied to field plots. Effect of three fungicides was over 80% with control value for controlling gray snow mold on Kentucky bluegrass and creeping bentgrass species. Effect of fungicide mixture with different family groups had an over 93% control value of gray snow mold on Kentucky bluegrass species. It was not significantly difference in fungicidal effect according to applied method (irrigation and spray) with azoxystrobin on Kentucky bluegrass and creeping bentrasss species. Effect of fungicides applied time was a significantly difference on disease control by tebconazole early fall spray.

A Study on Using Gray Color Dyeing from Gallapple (오배자에 의한 회색계열 염색에 관한 연구)

  • Shin, Nam-Hee;Kim, Sung-Yeon;Cho, Kuyung-Rae
    • Fashion & Textile Research Journal
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    • v.7 no.5
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    • pp.547-552
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    • 2005
  • The study has objective in raising value of the gray color as a meaningful color suiting sentiments of modern people by expressing the gray color in various perspective utilizing natural dyes that is natural at the same time having aesthetic color tones. For example, the main ingredient used for coloring black and gray color is the pyrogallol tannin and the gray tone dye can be acquired by combining the tannin with iron. In order to find the suitable condition for processing tannin, UV-Vis part absorption spectrum of Gallapple pyrogallol tannin, dye ability based on temperature and time, reflection rate based on concentration, color changes based on acid treatment and alkali treatment, changes on surface based on concentration or metal mordant condition, and lightfastness were measured. Maximum absorption wavelength (${\lambda}_{max}$) of Gallapple tannin was at around 273 nm, while strong absorption was also observed at below 350 nm. Dye ability of Gallapple tannin is done more easily on silk rather than cellulose fibers such as cotton, while the optimum condition for dyeing was observed to be at $60^{\circ}C$, for 20 minutes. As a result of acid treatment, the color of dye material consist highly of gray tones and showed red tone after the alkali treatment. While it was observed that as dye concentration and metal mordant concentration increased the color changed at counter-clockwise direction on the Y-scale of Munsell's scale of colors. Lightfastness was more on a normal fading. I hope this study opens up possibilities towards presenting gray color expressed from tannin as color with diversity and aesthetic value. In future, comparative study between dye expressed from catechol tannin dye materials will be helpful.

CORRELATION ASSESSMENT BETWEEN RESONANCE FREQUENCY ANALYSIS AND RADIOGRAPHIC METHOD ACCORDING TO PERI-IMPLANT BONE CHANGE

  • Lee Mi-Ran;Cho Lee-Ra;Yi Yang-Jin;Choi Hang-Moon;Park Chan-Jin
    • The Journal of Korean Academy of Prosthodontics
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    • v.43 no.6
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    • pp.736-744
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    • 2005
  • Statement of problem. Initial stability of implant is an important factor for predicting osseointegration. It requires a rapid, non-invasive, user-friendly technique to frequently assess the implant stability and the degree of osseointegration. Purpose. The aim of this study was to evaluate the correlation between the resonance frequency analysis (RFA) and the radiographic method for peri-implant bone change under in vitro conditions. Material and Method. Twenty implants of 3.75 mm in diameter(Neoplant, Neobiotech, Korea) were used. To simulate peri-implant bone change, 2 mm-deep $45^{\circ}$ range horizontal defect and 2 mm-deep $90^{\circ}$ range horizontal defect area were serially prepared perpendicular to the X-ray beam after conventional implant insertion. Customized film holding device was fabricated to standardize the projection geometry for serial radiographs of implants and direct digital image was obtained. ISQ values and gray values inside threads were measured before and after peri-implant bone defect preparation. Results. Within a limitation of this study, ISQ value of resonance frequency analysis was changed according to peri-implant bone change (p<0.05) and gray value of radiographic method was changed according to peri-implant bone change (p<0.05). There was no correlation between the ISQ value and the gray value for peri-implant bone change (p>0.05). But, in horizontal defect condition, relatively positive correlation were between ISQ and gray values(r=0.663). Conclusion. This results provided a possibility that peri-implant bone change may be evaluated by both RFA and radiographic method.

Automatic Liver Segmentation by using Gray Value Portion in Enhanced Abdominal CT Image (조영제를 사용한 복부CT영상에서 명암값 비율을 이용한 간의 자동 추출)

  • Yu, Seung-Hwa;Jo, Jun-Sik;No, Seung-Mu;Sin, Gyeong-Suk;Park, Jong-Won
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.38 no.2
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    • pp.179-190
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    • 2001
  • In this proposed study, observing and analyzing contrast enhanced abdominal CT images, we segmented the liver automatically. We computed the ratio of each gray value from the estimated gray value range. With the average value of mesh image, we distinguished the liver from the noise parts. We divided the region based on immersion simulation. The threshold value is determined from the mesh image which is generated from each gray value portion of the liver and is used in dividing the liver to the noise region. To get the outline of the liver, we generated template image which represents the lump of the liver, and subtracted it from the binary image. With the results we use the proposed algorithm using 8-connectivity instead of the present opening algorithm, to reduce the processing time. We computed the volume from the segmented organ size and presented a clinical demonstration with the animal experiment

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