메뉴 건너뛰기




Volumn 26, Issue 1, 2012, Pages 81-90

Application of image texture analysis for varietal classification of barley

Author keywords

Automated kernel grading; Barley; Digital image analysis; Discrimination; Image texture analysis

Indexed keywords

BARLEY; DIGITAL IMAGE; DISCRIMINANT ANALYSIS; IMAGE ANALYSIS; TEXTURE;

EID: 84859704782     PISSN: 02368722     EISSN: None     Source Type: Journal    
DOI: 10.2478/v10247-012-0012-z     Document Type: Article
Times cited : (15)

References (18)
  • 3
    • 39149135828 scopus 로고    scopus 로고
    • Classification of cereal grains using wavelet, morphological, colour, and textural features of non-touching kernel images
    • Choudhary R., Paliwal J., and Jayas D.S., 2009. Classification of cereal grains using wavelet, morphological, colour, and textural features of non-touching kernel images. Biosys. Eng., 99, 330-337.
    • (2009) Biosys. Eng , vol.99 , pp. 330-337
    • Choudhary, R.1    Paliwal, J.2    Jayas, D.S.3
  • 4
    • 71649108154 scopus 로고    scopus 로고
    • Assessing breakage and cracks of parboiled rice kernels by image analysis techniques
    • Courtois F., Faessel M., and Bonazzi C., 2010. Assessing breakage and cracks of parboiled rice kernels by image analysis techniques. Food Control, 21, 567-572.
    • (2010) Food Control , vol.21 , pp. 567-572
    • Courtois, F.1    Faessel, M.2    Bonazzi, C.3
  • 5
    • 76149131021 scopus 로고    scopus 로고
    • Monitoring geometric characteristics of rice during processing by image analysis system and micrometer measurement
    • Emadzadeh B., Razavi S.M.A., and Farahmandfar R., 2010. Monitoring geometric characteristics of rice during processing by image analysis system and micrometer measurement. Int. Agrophys., 24, 21-27.
    • (2010) Int. Agrophys , vol.24 , pp. 21-27
    • Emadzadeh, B.1    Razavi, S.M.A.2    Farahmandfar, R.3
  • 6
    • 0015395891 scopus 로고
    • Considerations of sample and feature size
    • Foley D.H., 1972. Considerations of sample and feature size. IEEE Trans. Information Theory, 18, 618-626.
    • (1972) IEEE Trans. Information Theory , vol.18 , pp. 618-626
    • Foley, D.H.1
  • 7
    • 33947695274 scopus 로고    scopus 로고
    • Analysis of plant tissue images obtained by confocal tandem scanning reflected light microscope
    • Gancarz M., Konstankiewicz K., Pawlak K., and Zdunek A., 2007. Analysis of plant tissue images obtained by confocal tandem scanning reflected light microscope. Int. Agrophysics, 21, 49-53.
    • (2007) Int. Agrophysics , vol.21 , pp. 49-53
    • Gancarz, M.1    Konstankiewicz, K.2    Pawlak, K.3    Zdunek, A.4
  • 8
    • 0001130002 scopus 로고    scopus 로고
    • Multi-layer neural networks for image analysis of agricultural products
    • Jayas D.S., Paliwal J., and Visen N.S., 2000. Multi-layer neural networks for image analysis of agricultural products. J. Agric. Eng. Res., 77(2), 119-128.
    • (2000) J. Agric. Eng. Res , vol.77 , Issue.2 , pp. 119-128
    • Jayas, D.S.1    Paliwal, J.2    Visen, N.S.3
  • 9
    • 0035606923 scopus 로고    scopus 로고
    • Classification of tough and tender beef by image texture analysis
    • Li J., Tan J., and Shatadal P., 2001. Classification of tough and tender beef by image texture analysis. Meat Sci., 57, 341-346.
    • (2001) Meat Sci , vol.57 , pp. 341-346
    • Li, J.1    Tan, J.2    Shatadal, P.3
  • 10
    • 0034473332 scopus 로고    scopus 로고
    • Classification of cereal grains using machine vision: I. Morphology models
    • Majumdar S. and Jayas D.S., 2000a. Classification of cereal grains using machine vision: I. Morphology models. Am. Soc. Agric. Eng., 43(6), 1669-1675.
    • (2000) Am. Soc. Agric. Eng , vol.43 , Issue.6 , pp. 1669-1675
    • Majumdar, S.1    Jayas, D.S.2
  • 11
    • 0034471670 scopus 로고    scopus 로고
    • Classification of cereal grains using machine vision: II. Color Models. Morphology models
    • Majumdar S. and Jayas D.S., 2000b. Classification of cereal grains using machine vision: II. Color Models. Morphology models. Am. Soc. Agric. Eng., 43(6), 1677-1680.
    • (2000) Am. Soc. Agric. Eng , vol.43 , Issue.6 , pp. 1677-1680
    • Majumdar, S.1    Jayas, D.S.2
  • 12
    • 0034473489 scopus 로고    scopus 로고
    • Classification of cereal grains using machine vision: III. Texture Models. Morphology models
    • Majumdar S. and Jayas D.S., 2000c. Classification of cereal grains using machine vision: III. Texture Models. Morphology models. Am. Soc. Agric. Eng., 43(6), 1681-1687.
    • (2000) Am. Soc. Agric. Eng , vol.43 , Issue.6 , pp. 1681-1687
    • Majumdar, S.1    Jayas, D.S.2
  • 13
    • 0007367697 scopus 로고    scopus 로고
    • Technical University of Łódź, Institute of Electronics, COST B11 report, Brussels, Belgium
    • Materka A. and Strzelecki M., 1998. Texture Analysis Methods - A Review. Technical University of Łódź, Institute of Electronics, COST B11 report, Brussels, Belgium.
    • (1998) Texture Analysis Methods - a Review
    • Materka, A.1    Strzelecki, M.2
  • 15
    • 85025482020 scopus 로고
    • Wheat grain color analysis by digital image processing: II. Wheat class determination
    • Neuman M., Sapristein H.D., Shwedyk E., and Bushuk W., 1989b. Wheat grain color analysis by digital image processing: II. Wheat class determination. J. Cereal Sci., 10(3), 183-188.
    • (1989) J. Cereal Sci , vol.10 , Issue.3 , pp. 183-188
    • Neuman, M.1    Sapristein, H.D.2    Shwedyk, E.3    Bushuk, W.4
  • 16
    • 0036680699 scopus 로고    scopus 로고
    • Description of food surfaces and microstructural changes using fractal image texture analysis
    • Quevedo R., Carlos L.G., Aguilera J.M., and Cadoche L., 2002. Description of food surfaces and microstructural changes using fractal image texture analysis. J. Food Eng., 53, 361-371.
    • (2002) J. Food Eng , vol.53 , pp. 361-371
    • Quevedo, R.1    Carlos, L.G.2    Aguilera, J.M.3    Cadoche, L.4
  • 17


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.