• Title/Summary/Keyword: Leaf Tobacco Grading

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Feasibility in Grading the Burley Type Dried Tobacco Leaf Using Computer Vision (컴퓨터 시각을 이용한 버얼리종 건조 잎 담배의 등급판별 가능성)

  • 조한근;백국현
    • Journal of Biosystems Engineering
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    • v.22 no.1
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    • pp.30-40
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    • 1997
  • A computer vision system was built to automatically grade the leaf tobacco. A color image processing algorithm was developed to extract shape, color and texture features. An improved back propagation algorithm in an artificial neural network was applied to grade the Burley type dried leaf tobacco. The success rate of grading in three-grade classification(1, 3, 5) was higher than the rate of grading in six-grade classification(1, 2, 3, 4, 5, off), on the average success rate of both the twenty-five local pixel-set and the sixteen local pixel-set. And, the average grading success rate using both shape and color features was higher than the rate using shape, color and texture features. Thus, the texture feature obtained by the spatial gray level dependence method was found not to be important in grading leaf tobacco. Grading according to the shape, color and texture features obtained by machine vision system seemed to be inadequate for replacing manual grading of Burely type dried leaf tobacco.

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Development of Tobacco Ripeness Grading Meter Using the Color Sensor (칼라센서를 이용한 담배 완숙도의 식별장치 개발)

  • 이대원;이용국
    • Journal of the Korean Society of Tobacco Science
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    • v.16 no.1
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    • pp.26-33
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    • 1994
  • A tobacco ripeness grading meter was designed and constructed using the color sensor, its performance was evaluated. A degree of ripeness grading of a leaf is very closely related to the measured tobacco leaf color. Measuring the small amount of the reflectance precisely depends on the apparatus including color sensor, light source, detector sensitivity, and geometric characteristics of appratus. To analyze and minimize the variational effects, experiments to select the proper condition were performed. Because of the combined effect mentioned above, the system has some variation on its response. Basis on the results of the experiments, prototype was developed and interfaced to a computer system. The main components of prototype included a tungsten lamp as a light source, Amorphous full color sensor with three filters, regulated D.C. power supply, OP - AMP(741 TC) for amplification, AR - B3001 board for interfacing to a computer with analog to digital conversion, and a compatible IBM PC XT computer. The experimental results of the developed ripeness tobacco leaf measurement system are summarized as following: [1] The output readings of ripeness grade meter for tobacco leaf, which is based on harvesting time, showed the apparent difference in variety of different quality. It was considered suitable that three filters(red, green, blue) in Amorphous full color sensor could be used in four different ripeness degree measurement of tobacco leaf. [2] The output readings of ripeness grade meter for tobacco leaf, which is based on government procurement, showed apparent difference in variety of different quality. Tobacco leaf varieties to stalk position are divided into tips, leaf, cutters, and primings, It is considered suitable that only red filter in the sensor could be used to classify the grade of tobacco leaf within the same kind tobacco stalk. However, the ripeness grade meter was not adequate to classify all the tobacco grades in the four different tobacco leaves.

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POSITION RECOGNITION AND QUALITY EVALUATION OF TOBACCO LEAVES VIA COLOR COMPUTER VISION

  • Lee, C. H.;H. Hwang
    • Proceedings of the Korean Society for Agricultural Machinery Conference
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    • 2000.11c
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    • pp.569-577
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    • 2000
  • The position of tobacco leaves is affluence to the quality. To evaluate its quality, sample leaves was collected according to the position of attachment. In Korea, the position was divided into four classes such as high, middle, low and inside positioned leaves. Until now, the grade of standard sample was determined by human expert from korea ginseng and tobacco company. Many research were done by the chemical and spectrum analysis using NIR and computer vision. The grade of tobacco leaves mainly classified into 5 grades according to the attached position and its chemical composition. In high and low positioned leaves shows a low level grade under grade 3. Generally, inside and medium positioned leaf has a high level grade. This is the basic research to develop a real time tobacco leaves grading system combined with portable NIR spectrum analysis system. However, this research just deals with position recognition and grading using the color machine vision. The RGB color information was converted to HSI image format and the sample was all investigated using the bundle of tobacco leaves. Quality grade and position recognition was performed through well known general error back propagation neural network. Finally, the relationship about attached leaf position and its grade was analyzed.

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Recognition of Tabacco Ripeness & Grading based on the Neural Network (신경회로망을 이용한 담배 숙도인식 및 등급판정)

  • LEE, S.S.;LEE, C.H.;LEE, D.W.;HWANG, H.
    • Journal of the Korean Society of Tobacco Science
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    • v.17 no.1
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    • pp.5-14
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    • 1995
  • Efficient algorithms for the automatic classification of flue-cured tovacco ripeness and grading have been developed The ripeness of the tobacco was classified into 4 levels vased on the color. The lab-built simple RGB color measuring system was utilized for detecting the light reflectance of the tobacco leaves. The measured data were used far training the artificial neural network The performance of the trained network was also tested far the untrained samples. The spectrophotometer was used to detect the light reflectance and absorption of the graded tobacco leaves in the frequency ranges of the visible light The measured data and the statistical analysis was performed to investigate the light characteristics of the graded samples. The measured data were obtained from samples of 5 different grades directly without considering the leaf positions. Those data were used far training the artificial neural network The performance of the trained network was also tested far the untrained samples. The neural network based sensor information processing showed successful results for grading of tobacco leaves.

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THE COMPARISONS OF VOLATILE OILS OF FLUE-CURED TOBACCO PRODUCED IN KOREA AND IN THE UNITED STATES (한미산 황색종 잎담배의 휘발성 정유성분 비교연구)

  • 장기운
    • Journal of the Korean Society of Tobacco Science
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    • v.7 no.2
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    • pp.151-167
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    • 1985
  • Generally, the same quality tobacco may give similar concentration of each chemical component. This research investigation was studied to obtain the differences in concentrations of volatile oil compounds in physically similar tobacco produced in different environment and managements-in Korea and in the United States. The flue-cured leaf tobacco produced in Korea and America was regraded to B3L and P3L by American grading system and analyzed for volatile oils relating to tobacco flavor and aroma. Sixty compounds of the more than 100 peaks distinguishable on the total neutral volatile oils were identified by G5-MS and quantified. Their concentrations are compared between B3 L and P3L produced in Korea and in the United States. The most volatile oil concentrations of B3 L and P3L grade tobacco arc higher in American than in Korean. Only a few components such as benzaldehyde, pulegonc, 4, 6, 9 - megastigmatriene - 3 - one, and coumaran are less in American.

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Extraction of Geometric and Color Features in the Tobacco-leaf by Computer Vision (컴퓨터 시각에 의한 잎담배의 외형 및 색 특징 추출)

  • Cho, H.K.;Song, H.K.
    • Journal of Biosystems Engineering
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    • v.19 no.4
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    • pp.380-396
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    • 1994
  • A personal computer based color machine vision system with video camera and fluorescent lighting system was used to generate images of stationary tobacco leaves. Image processing algorithms were developed to extract both the geometric and the color features of tobacco leaves. Geometric features include area, perimeter, centroid, roundness and complex ratio. Color calibration scheme was developed to convert measured pixel values to the standard color unit using both statistics and artificial neural network algorithm. Improved back propagation algorithm showed less sum of square errors than multiple linear regression. Color features provide not only quality evaluation quantities but the accurate color measurement. Those quality features would be useful in grading tobacco automatically. This system would also be useful in measuring visual features of other agricultural products.

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Effect of Various Application Rates of Nitrogen, Phosphorus, and Potassium on Quality and Chemical Components of Flue-Cured Tobacco (질소(窒素), 인산(燐酸), 가리(加里)의 시비비율(施肥比率)이 황색종연초(黃色種煙草)의 품질(品質)과 화학적(化學的) 조성(組成)에 미치는 영향(影響))

  • Jeong, Hun-Chae;Cho, Seong-Jin;Lee, Yun-Hwan;Yuk, Chang-Soo
    • Korean Journal of Soil Science and Fertilizer
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    • v.19 no.1
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    • pp.63-69
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    • 1986
  • 1. Chemical components of fresh tobacco leaves at topping stages were affected variously by fertilizer application level. The more fertilizers were applicated, the higher nitrogen content of leaves was shown regardless of the soil fertility, but phosphorus content was not affected either by phosphorus rate or soil fertility. Potassium content was higher in the leaves grown in fertile soil than infertile at the same application rate. 2. Maturation of tobacco leaves was delayed by applying high level of nitrogen fertilizer, especially in fertile soil. The excessive accumulation of nitrogen in tobacco leaves at later stage of growth resulted in poor quality index for the high content of nicotine and low content of reducing sugar in cured leaves. 3. Nicotine content of cured leaf was increased significantly as nitrogen content increased, regardless of soil fertility, but reducing sugar content was reduced. Nicotine and reducing sugar content of cured leaf were higher in fertile than in infertile soil. 4. Resulting from the facts that nicotine contents were negatively correlated and reducing sugar contents were positively correlated with grading value (Won/Kg), authors suggested that grading index (Won/Kg) of the Office of Monopoly be based on quality index from chemical components of cured leaves.

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