• Title/Summary/Keyword: Color Determination

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Determination of Chemical Composition of Toasted Burley Tobacco by Near Infrared Spectroscopy (근적외선분광법을 이용한 버어리 토스트엽의 화학성분 분석)

  • 김용옥;정한주;백순옥;김기환
    • Journal of the Korean Society of Tobacco Science
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    • v.17 no.2
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    • pp.177-183
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    • 1995
  • This study was conducted to develop the most precise NIR(near infrared spectrometric) calibration for rapid determination of chemical composition in ground samples of toasted burley tobacco using stepwise, stepup, principal component regression(PCR), partial least square(PLS) and modified partial least square(MPLS) calibration method. The number of wavelength(W) selected by stepup multiple linear regression using: second derivative spectra was as follows: total sugar(TS)-4 W, nicotine-9 W, total nitrogen(TN)-2 W, ash-8 W, total volatile base(TVB)-5 W, chlorine4 W, L of color-6 W, a of color-6 W and b of color-7 W. Comparing the calibration equations followed by each chemical components, the most precise calibration equation was MPLS for 75, a and b of color, PLS for nicotine, ash, TVB, chlorine and L of color and stepup for TN. The standard error of calibration(SEC) and standard error of performance(SEP) between result of near infrared analysis and standard laboratory analysis were 0.18, 0.40% for 75, 0.06, 0.08% for nicotine, 0.18, 0.16% for TN, 0.33, 0.46% for ash, 0.04, 0.03% for TVB, 0.08, 0.06% for chlorine, 0.54, 0.58 for L of color, 0.22, 0.22 for a of color and 0.27, 0.27 for b of color, respectively. The SEC and SEP of ash and TVB were within allowable error of standard laboratory analysis, nicotine, TN and chlorine were 1.2-2.0 times and 75 were 2.1-4.0 times larger than allowable error of standard laboratory analysis. The ratio of SEC and SEP to mean were 1.5, 1.6% for L of color, 3.7, 3.8% for a of color and 1.8, 1.8% for b of color, respectively. Key words : burley tobacco chemistry, near infrared spectroscopy.

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A Study on the Color Membership Computation Method using Fuzzy Color Model (패지 컬러 모델을 이용한 컬러의 소속 정도를 결정하는 방법에 관한 연구)

  • Kim, Dae-Won;Lee, Kwang. H.
    • Proceedings of the Korean Information Science Society Conference
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    • 2002.04b
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    • pp.262-264
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    • 2002
  • In this paper we focused on the color representation prob1em based on fuzzy set theory. The main factor is the determination or computation of color membership function and color difference formula. The mathematical formula to calculate the color difference should generate a uniform color scaling, and due to this reason we adopted a CIELAB color- space as a fundamental feature space. With the help of the CIELAB color space we created a new color model, referred to fuzzy color model, which can represent the ambiguous characteristics underlying colors. Based on the proposed color difference formula between fuzzy colors, we could obtain the membership computation method of an arbitrary color for a given color family.

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Studies on the Colorimetric Determination of Panaxadiol and Panaxatriol (Panaxadiol 및 Panaxatriol의 비색정량법에 관한 연구)

  • 남성희;유병무;김해중;이석건
    • Journal of Ginseng Research
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    • v.3 no.2
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    • pp.127-133
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    • 1979
  • A simple and rapid colorimetric method for determination of panaxadiol and , panaxadiol was developed. 1. After heating with 60% perchloric acid, panaxadiol and panaxadiol yielded red.purple color with absorption maximum at 540 nm and 538 nm, respectively. 2. The maximum colors of the Panaxadiol and panaxadiol were reached when the algycones were treated at 6$0^{\circ}C$, 5 minutes or 7$0^{\circ}C$ 3 minutes. 3. The absorbance varied linearly with the amount of aglycone in the reaction mixture. And the colorimetric method was sensitive to about 10$\mu\textrm{g}$ of aglycone in 5.5ml of the reaction mixture. 4. The color was stable for about a week at 4$^{\circ}C$. 5. $\beta$-Sitosterol, oleanolic acid and cholesterol were not yielded red color by treatment with 60% perchloric acid under the conditions described.

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Color Determination of Beef Rib Eye Using Near Infrared Spectroscopy

  • Kang, J.O.;Park, J.Y.;Choy, Y.H.
    • Asian-Australasian Journal of Animal Sciences
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    • v.14 no.2
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    • pp.263-267
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    • 2001
  • Beef samples of loin eye area from New Zealand, USA and three quality grades of Hanwoo were analyzed using near infrared spectrophotometer with reference values from laboratory optical Chromameter to determine effective spectrum range and mathematical treatment for determination of color values. $R^2s$ of prediction models were not improved much by calibrating with whole light range (400~2500 nm) compared to using visible range (400~1100 nm). Standard errors of calibration and prediction were influenced by possible bias due to sampling non-homogeneous sample sources. However, partial differentiation in the first order was more stable against sampling biases than second derivatives of the spectra. Lightness value was little different among the five sample sources of beef. Beef samples from USA were brighter and more reddish than beefs of Hanwoo or from New Zealand (p<0.05). Yellowness of USA beef was the highest followed by beef from New Zealand, which was also higher than Hanwoo beefs of three quality grades (p<0.05).

Determination of threshold values for color image segmentation (색도 영상분할을 위한 문턱치 결정방법)

  • 이병욱
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.21 no.4
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    • pp.869-875
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    • 1996
  • This paper investigates a method for dtermining a threshold value based on the probability distribution function for color image segmentation. Principal components of normalized color is nalyzed and found that there are effective color transforms for outdoor scents. We esplain the functional relationship of the treshold and the probability of a regiona detection, asuming bivarate Gaussian probability density function. Experimental results show that the probability of detection is proportional to the segmented area.

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Color Modeling of Milled Rice by Milling Degree (도정도에 따른 쌀의 칼라 모델링)

  • Kim, Oui-Woung;Kim, Hoon;Lee, Se-Eun
    • Food Science and Preservation
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    • v.12 no.2
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    • pp.141-145
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    • 2005
  • To investigate the relationship between the milling degree and color of milled rice, an empirical whiteness model was developed according to the milling degree from $0\%\;to\;20\%$ using paddy of three different varieties of Chuchung, Nampyong and Odae. The values of determination coefficient and the root mean square error between measured and predicted whiteness were 0.990, 0.877, respectively, and the whiteness model was proved to be quite applicable. The relationships between whiteness values and color factors in several color systems were tested to select useful color factors for development of convenient whiteness meter. The whiteness value of milled rice according to degree of milling could be converted into b and Hunter whiteness in Lab color system. B in RGB color system at high values of determination coefficient were 0.990, 0.985, and 0.989, respectively.

Real time detection and recognition of traffic lights using component subtraction and detection masks (성분차 색분할과 검출마스크를 통한 실시간 교통신호등 검출과 인식)

  • Jeong Jun-Ik;Rho Do-Whan
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.43 no.2 s.308
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    • pp.65-72
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    • 2006
  • The traffic lights detection and recognition system is an essential module of the driver warning and assistance system. A method which is a color vision-based real time detection and recognition of traffic lights is presented in this paper This method has four main modules : traffic signals lights detection module, traffic lights boundary candidate determination module, boundary detection module and recognition module. In traffic signals lights detection module and boundary detection module, the color thresholding and the subtraction value of saturation and intensity in HSI color space and detection probability mask for lights detection are used to segment the image. In traffic lights boundary candidate determination module, the detection mask of traffic lights boundary is proposed. For the recognition module, the AND operator is applied to the results of two detection modules. The input data for this method is the color image sequence taken from a moving vehicle by a color video camera. The recorded image data was transformed by zooming function of the camera. And traffic lights detection and recognition experimental results was presented in this zoomed image sequence.

Machine's Determination of Main Color and Imbalance in a Drawing for Art Psychotherapy (그림진단을 위한 주제색 및 불균형 판단의 자동화)

  • Bae Jun;Kim Jae Min;Kim Seong-in
    • Journal of Institute of Control, Robotics and Systems
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    • v.12 no.2
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    • pp.119-129
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    • 2006
  • Art psychotherapy is widely accepted as an effective tool for diagnosis and treatment of psychological disorders. Important factors for art psychotherapy diagnosis, based on the projection theory that the world of the inner mind appears in drawings, include main color and imbalance of a drawing. This paper develops a system for a machine to determine the main color and the imbalance of a drawing by color recognition and edge detection. Our proposed color recognition procedure adopts NBS(National Bureau of Standards) distance between colors in HVC(Hue, Value, Chroma) color space which is most similar to the human eye's color perception. Our edge detection procedure applies blurring, clustering and transformation to a standard color in a series. Our system considers the numbers of pixels and clusters for each color as a criterion for main color and the frequency of edge coordinates for each region for imbalance. The proposed machine procedure, verified through case studies, can help overcome the subjectivity, ambiguity and uncertainty in human decision involved in art psychotherapy.

Human Head Mouse System Based on Facial Gesture Recognition

  • Wei, Li;Lee, Eung-Joo
    • Journal of Korea Multimedia Society
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    • v.10 no.12
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    • pp.1591-1600
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    • 2007
  • Camera position information from 2D face image is very important for that make the virtual 3D face model synchronize to the real face at view point, and it is also very important for any other uses such as: human computer interface (face mouth), automatic camera control etc. We present an algorithm to detect human face region and mouth, based on special color features of face and mouth in $YC_bC_r$ color space. The algorithm constructs a mouth feature image based on $C_b\;and\;C_r$ values, and use pattern method to detect the mouth position. And then we use the geometrical relationship between mouth position information and face side boundary information to determine the camera position. Experimental results demonstrate the validity of the proposed algorithm and the Correct Determination Rate is accredited for applying it into practice.

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Determination of Leaf Color and Health State of Lettuce using Machine Vision (기계시각을 이용한 상추의 엽색 및 건강상태 판정)

  • Lee, J.W.
    • Journal of Biosystems Engineering
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    • v.32 no.4
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    • pp.256-262
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    • 2007
  • Image processing systems have been used to measure the plant parameters such as size, shape and structure of plants. There are yet some limited applications for evaluating plant colors due to illumination conditions. This study was focused to present adaptive methods to analyze plant leaf color regardless of illumination conditions. Color patches attached on the calibration bars were selected to represent leaf colors of lettuces and to test a possibility of health monitoring of lettuces. Repeatability of assigning leaf colors to color patches was investigated by two-tailed t-test for paired comparison. It resulted that there were no differences of assignment histogram between two images of one lettuce that were acquired at different light conditions. It supported that use of the calibration bars proposed for leaf color analysis provided color constancy, which was one of the most important issues in a video color analysis. A health discrimination equation was developed to classify lettuces into one of two classes, SOUND group and POOR group, using the machine vision. The classification accuracy of the developed health discrimination equation was 80.8%, compared to farmers' decision. This study could provide a feasible method to develop a standard color chart for evaluating leaf colors of plants and plant health monitoring system using the machine vision.