메뉴 건너뛰기




Volumn 144, Issue , 2016, Pages 52-60

A review on the main challenges in automatic plant disease identification based on visible range images

Author keywords

Automatic identification; Digital image processing; Plant diseases; Visible symptoms

Indexed keywords

AUTOMATION; IMAGE SEGMENTATION;

EID: 84958554797     PISSN: 15375110     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.biosystemseng.2016.01.017     Document Type: Review
Times cited : (497)

References (69)
  • 1
    • 0032894146 scopus 로고    scopus 로고
    • Color classifier for symptomatic soybean seeds using image processing
    • Ahmad I.S., Reid J.F., Paulsen M.R., Sinclair J.B. Color classifier for symptomatic soybean seeds using image processing. Plant Disease 1999, 83(4):320-327.
    • (1999) Plant Disease , vol.83 , Issue.4 , pp. 320-327
    • Ahmad, I.S.1    Reid, J.F.2    Paulsen, M.R.3    Sinclair, J.B.4
  • 2
    • 0036220619 scopus 로고    scopus 로고
    • Multispectral inspection of citrus in real-time using machine vision and digital signal processors
    • Aleixos N., Blasco J., Navarrón F., Moltó E. Multispectral inspection of citrus in real-time using machine vision and digital signal processors. Computers and Electronics in Agriculture 2002, 33:121-137.
    • (2002) Computers and Electronics in Agriculture , vol.33 , pp. 121-137
    • Aleixos, N.1    Blasco, J.2    Navarrón, F.3    Moltó, E.4
  • 3
  • 4
    • 84891387582 scopus 로고    scopus 로고
    • Digital image processing techniques for detecting, quantifying and classifying plant diseases
    • Barbedo J.G.A. Digital image processing techniques for detecting, quantifying and classifying plant diseases. SpringerPlus 2013, 2:660.
    • (2013) SpringerPlus , vol.2 , pp. 660
    • Barbedo, J.G.A.1
  • 5
    • 84910626128 scopus 로고    scopus 로고
    • An automatic method to detect and measure leaf disease symptoms using digital image processing
    • Barbedo J.G.A. An automatic method to detect and measure leaf disease symptoms using digital image processing. Plant Disease 2014, 98:1709-1716.
    • (2014) Plant Disease , vol.98 , pp. 1709-1716
    • Barbedo, J.G.A.1
  • 6
    • 84922311189 scopus 로고    scopus 로고
    • Detecting fusarium head blight in wheat kernels using hyperspectral imaging
    • Barbedo J.G.A., Tibola C.S., Fernandes J.M.C. Detecting fusarium head blight in wheat kernels using hyperspectral imaging. Biosystems Engineering 2015, 131:65-76.
    • (2015) Biosystems Engineering , vol.131 , pp. 65-76
    • Barbedo, J.G.A.1    Tibola, C.S.2    Fernandes, J.M.C.3
  • 7
    • 84871926643 scopus 로고    scopus 로고
    • Thermography versus chlorophyll fluorescence imaging for detection and quantification of apple scab
    • Belin E., Rousseau D., Boureau T., Caffier V. Thermography versus chlorophyll fluorescence imaging for detection and quantification of apple scab. Computers and Electronics in Agriculture 2013, 90:159-163.
    • (2013) Computers and Electronics in Agriculture , vol.90 , pp. 159-163
    • Belin, E.1    Rousseau, D.2    Boureau, T.3    Caffier, V.4
  • 9
    • 0141564871 scopus 로고    scopus 로고
    • Use of digital images to differentiate reactions of collections of yellow starthistle (Centaurea solstitialis) to infection by Puccinia jaceae
    • Berner D.K., Paxson L.K. Use of digital images to differentiate reactions of collections of yellow starthistle (Centaurea solstitialis) to infection by Puccinia jaceae. Biological Control 2003, 28:171-179.
    • (2003) Biological Control , vol.28 , pp. 171-179
    • Berner, D.K.1    Paxson, L.K.2
  • 10
    • 67650047839 scopus 로고    scopus 로고
    • Automated image analysis of the severity of foliar citrus canker symptoms
    • Bock C.H., Cook A.Z., Parker P.E., Gottwald T.R. Automated image analysis of the severity of foliar citrus canker symptoms. Plant Disease 2009, 93(6):660-665.
    • (2009) Plant Disease , vol.93 , Issue.6 , pp. 660-665
    • Bock, C.H.1    Cook, A.Z.2    Parker, P.E.3    Gottwald, T.R.4
  • 11
    • 42149107432 scopus 로고    scopus 로고
    • Visual rating and the use of image analysis for assessing different symptoms of citrus canker on grapefruit leaves
    • Bock C.H., Parker P.E., Cook A.Z., Gottwald T.R. Visual rating and the use of image analysis for assessing different symptoms of citrus canker on grapefruit leaves. Plant Disease 2008, 92(4):530-541.
    • (2008) Plant Disease , vol.92 , Issue.4 , pp. 530-541
    • Bock, C.H.1    Parker, P.E.2    Cook, A.Z.3    Gottwald, T.R.4
  • 12
    • 77950942373 scopus 로고    scopus 로고
    • Plant disease severity estimated visually, by digital photography and image analysis, and by hyperspectral imaging
    • Bock C.H., Poole G.H., Parker P.E., Gottwald T.R. Plant disease severity estimated visually, by digital photography and image analysis, and by hyperspectral imaging. Critical Reviews in Plant Sciences 2010, 29:59-107.
    • (2010) Critical Reviews in Plant Sciences , vol.29 , pp. 59-107
    • Bock, C.H.1    Poole, G.H.2    Parker, P.E.3    Gottwald, T.R.4
  • 16
    • 77949852900 scopus 로고    scopus 로고
    • Domain adaptation problems: a DASVM classification technique and a circular validation strategy
    • Bruzzone L., Marconcini M. Domain adaptation problems: a DASVM classification technique and a circular validation strategy. IEEE Transactions on Pattern Analysis and Machine Intelligence 2010, 32(5):770-787.
    • (2010) IEEE Transactions on Pattern Analysis and Machine Intelligence , vol.32 , Issue.5 , pp. 770-787
    • Bruzzone, L.1    Marconcini, M.2
  • 17
    • 57449114907 scopus 로고    scopus 로고
    • An image-processing based algorithm to automatically identify plant disease visual symptoms
    • Camargo A., Smith J.S. An image-processing based algorithm to automatically identify plant disease visual symptoms. Biosystems Engineering 2009, 102:9-21.
    • (2009) Biosystems Engineering , vol.102 , pp. 9-21
    • Camargo, A.1    Smith, J.S.2
  • 19
    • 84925945623 scopus 로고    scopus 로고
    • A new colour vision system to quantify automatically foliar discolouration caused by insect pests feeding on leaf cells
    • Clément A., Verfaille T., Lormel C., Jaloux B. A new colour vision system to quantify automatically foliar discolouration caused by insect pests feeding on leaf cells. Biosystems Engineering 2015, 133:128-140.
    • (2015) Biosystems Engineering , vol.133 , pp. 128-140
    • Clément, A.1    Verfaille, T.2    Lormel, C.3    Jaloux, B.4
  • 20
    • 77958460469 scopus 로고    scopus 로고
    • Image processing methods for quantitatively detecting soybean rust from multispectral images
    • Cui D., Zhang Q., Li M., Hartman G.L., Zhao Y. Image processing methods for quantitatively detecting soybean rust from multispectral images. Biosystems Engineering 2010, 107:186-193.
    • (2010) Biosystems Engineering , vol.107 , pp. 186-193
    • Cui, D.1    Zhang, Q.2    Li, M.3    Hartman, G.L.4    Zhao, Y.5
  • 22
    • 79951727131 scopus 로고    scopus 로고
    • Detection of head blight (Fusarium ssp.) in winter wheat by color and multispectral image analyses
    • Dammera K.-H., Möller B., Rodemann B., Heppner D. Detection of head blight (Fusarium ssp.) in winter wheat by color and multispectral image analyses. Crop Protection 2011, 30:420-428.
    • (2011) Crop Protection , vol.30 , pp. 420-428
    • Dammera, K.-H.1    Möller, B.2    Rodemann, B.3    Heppner, D.4
  • 23
    • 84855850003 scopus 로고    scopus 로고
    • The use of digital image analysis and real-time PCR fine-tunes bioassays for quantification of Cercospora leaf spot disease in sugar beet breeding
    • De Coninck B.M.A., Amand O., Delauré S.L., Lucas S., Hias N., Weyens G., et al. The use of digital image analysis and real-time PCR fine-tunes bioassays for quantification of Cercospora leaf spot disease in sugar beet breeding. Plant Pathology 2011, 61(1):76-84.
    • (2011) Plant Pathology , vol.61 , Issue.1 , pp. 76-84
    • De Coninck, B.M.A.1    Amand, O.2    Delauré, S.L.3    Lucas, S.4    Hias, N.5    Weyens, G.6
  • 27
    • 84878353036 scopus 로고    scopus 로고
    • Illumination invariant segmentation of vegetation for time series wheat images based on decision tree model
    • Guo W., Rage U.K., Ninomiya S. Illumination invariant segmentation of vegetation for time series wheat images based on decision tree model. Computers and Electronics in Agriculture 2013, 96:58-66.
    • (2013) Computers and Electronics in Agriculture , vol.96 , pp. 58-66
    • Guo, W.1    Rage, U.K.2    Ninomiya, S.3
  • 28
    • 33947614142 scopus 로고    scopus 로고
    • Application of artificial neural network for detecting Phalaenopsis seedling diseases using color and texture features
    • Huang K.Y. Application of artificial neural network for detecting Phalaenopsis seedling diseases using color and texture features. Computers and Electronics in Agriculture 2007, 57:3-11.
    • (2007) Computers and Electronics in Agriculture , vol.57 , pp. 3-11
    • Huang, K.Y.1
  • 38
    • 0031972345 scopus 로고    scopus 로고
    • Microcomputer-based quantification of maize streak virus symptoms in Zea mays
    • Martin D.P., Rybicki E.P. Microcomputer-based quantification of maize streak virus symptoms in Zea mays. Phytopathology 1998, 88(5):422-427.
    • (1998) Phytopathology , vol.88 , Issue.5 , pp. 422-427
    • Martin, D.P.1    Rybicki, E.P.2
  • 39
    • 21244478576 scopus 로고    scopus 로고
    • Assessment of the disease severity of squash powdery mildew through visual analysis, digital image analysis and validation of these methodologies
    • Moya E.A., Barralesa L.R., Apablaza G.E. Assessment of the disease severity of squash powdery mildew through visual analysis, digital image analysis and validation of these methodologies. Crop Protection 2005, 24:785-789.
    • (2005) Crop Protection , vol.24 , pp. 785-789
    • Moya, E.A.1    Barralesa, L.R.2    Apablaza, G.E.3
  • 40
    • 84897950977 scopus 로고    scopus 로고
    • Automatic detection of powdery mildew on grapevine leaves by image analysis: optimal view-angle range to increase the sensitivity
    • Oberti R., Marchi M., Tirelli P., Calcante A., Iriti M., Borghese A.N. Automatic detection of powdery mildew on grapevine leaves by image analysis: optimal view-angle range to increase the sensitivity. Computers and Electronics in Agriculture 2014, 104:1-8.
    • (2014) Computers and Electronics in Agriculture , vol.104 , pp. 1-8
    • Oberti, R.1    Marchi, M.2    Tirelli, P.3    Calcante, A.4    Iriti, M.5    Borghese, A.N.6
  • 41
    • 0035096961 scopus 로고    scopus 로고
    • Assessment of severity of powdery mildew infection of sweet cherry leaves by digital image analysis
    • Olmstead J.W., Lang G.A., Grove G.G. Assessment of severity of powdery mildew infection of sweet cherry leaves by digital image analysis. Hortscience 2001, 36(1):107-111.
    • (2001) Hortscience , vol.36 , Issue.1 , pp. 107-111
    • Olmstead, J.W.1    Lang, G.A.2    Grove, G.G.3
  • 45
    • 84875094732 scopus 로고    scopus 로고
    • Rice diseases classification using feature selection and rule generation techniques
    • Phadikar S., Sil J., Das A.K. Rice diseases classification using feature selection and rule generation techniques. Computers and Electronics in Agriculture 2013, 90:76-85.
    • (2013) Computers and Electronics in Agriculture , vol.90 , pp. 76-85
    • Phadikar, S.1    Sil, J.2    Das, A.K.3
  • 46
    • 84890832028 scopus 로고    scopus 로고
    • Automatic detection of tulip breaking virus (TBV) in tulip fields using machine vision
    • Polder G., van der Heijden G.W.A.M., van Doorn J., Baltissen T.A.H.M.C. Automatic detection of tulip breaking virus (TBV) in tulip fields using machine vision. Biosystems Engineering 2014, 117:35-42.
    • (2014) Biosystems Engineering , vol.117 , pp. 35-42
    • Polder, G.1    van der Heijden, G.W.2    van Doorn, J.3    Baltissen, T.A.4
  • 48
    • 84918785251 scopus 로고    scopus 로고
    • An evaluation of a vision-based sensor performance in Huanglongbing disease identification
    • Pourreza A., Lee W.S., Etxeberria E., Banerjee A. An evaluation of a vision-based sensor performance in Huanglongbing disease identification. Biosystems Engineering 2015, 130:13-22.
    • (2015) Biosystems Engineering , vol.130 , pp. 13-22
    • Pourreza, A.1    Lee, W.S.2    Etxeberria, E.3    Banerjee, A.4
  • 49
    • 33646118990 scopus 로고    scopus 로고
    • Identification of citrus disease using color texture features and discriminant analysis
    • Pydipati R., Burks T.F., Lee W.S. Identification of citrus disease using color texture features and discriminant analysis. Computers and Electronics in Agriculture 2006, 52(1-2):49-59.
    • (2006) Computers and Electronics in Agriculture , vol.52 , Issue.1-2 , pp. 49-59
    • Pydipati, R.1    Burks, T.F.2    Lee, W.S.3
  • 52
    • 56749097943 scopus 로고    scopus 로고
    • Pattern recognition method to detect two diseases in rice plants
    • Sanyal P., Patel S.C. Pattern recognition method to detect two diseases in rice plants. Imaging Science Journal 2008, 56(6):319-325.
    • (2008) Imaging Science Journal , vol.56 , Issue.6 , pp. 319-325
    • Sanyal, P.1    Patel, S.C.2
  • 53
  • 55
    • 42149092316 scopus 로고    scopus 로고
    • Comparing image format and resolution for assessment of foliar diseases of wheat
    • (online)
    • Steddom K., McMullen M., Schatz B., Rush C.M. Comparing image format and resolution for assessment of foliar diseases of wheat. Plant Health Progress 2005, (online). 10.1094/PHP-2005-0516-01-RS.
    • (2005) Plant Health Progress
    • Steddom, K.1    McMullen, M.2    Schatz, B.3    Rush, C.M.4
  • 57
    • 0000053531 scopus 로고    scopus 로고
    • Quantitative assessment of lesion characteristics and disease severity using digital image processing
    • Tucker C.C., Chakraborty S. Quantitative assessment of lesion characteristics and disease severity using digital image processing. Journal of Phytopathology 1997, 145:273-278.
    • (1997) Journal of Phytopathology , vol.145 , pp. 273-278
    • Tucker, C.C.1    Chakraborty, S.2
  • 60
    • 46549085311 scopus 로고    scopus 로고
    • Quantifying fungal infection of plant leaves by digital image analysis using Scion Image software
    • Wijekoon C.P., Goodwin P.H., Hsiang T. Quantifying fungal infection of plant leaves by digital image analysis using Scion Image software. Journal of Microbiological Methods 2008, 74:94-101.
    • (2008) Journal of Microbiological Methods , vol.74 , pp. 94-101
    • Wijekoon, C.P.1    Goodwin, P.H.2    Hsiang, T.3
  • 62
    • 79957444120 scopus 로고    scopus 로고
    • Use of leaf color images to identify nitrogen and potassium deficient tomatoes
    • Xu G., Zhang F., Shah S.G., Ye Y., Mao H. Use of leaf color images to identify nitrogen and potassium deficient tomatoes. Pattern Recognition Letters 2011, 32:1584-1590.
    • (2011) Pattern Recognition Letters , vol.32 , pp. 1584-1590
    • Xu, G.1    Zhang, F.2    Shah, S.G.3    Ye, Y.4    Mao, H.5
  • 63
    • 84937880107 scopus 로고    scopus 로고
    • Crop feature extraction from images with probabilistic superpixel Markov random field
    • Ye M., Cao Z., Yu Z., Bai X. Crop feature extraction from images with probabilistic superpixel Markov random field. Computers and Electronics in Agriculture 2015, 114:247-260.
    • (2015) Computers and Electronics in Agriculture , vol.114 , pp. 247-260
    • Ye, M.1    Cao, Z.2    Yu, Z.3    Bai, X.4
  • 65
    • 80053624014 scopus 로고    scopus 로고
    • Automatic citrus canker detection from leaf images captured in field
    • Zhang M., Meng Q. Automatic citrus canker detection from leaf images captured in field. Pattern Recognition Letters 2011, 32:2036-2046.
    • (2011) Pattern Recognition Letters , vol.32 , pp. 2036-2046
    • Zhang, M.1    Meng, Q.2
  • 67
    • 84888406369 scopus 로고    scopus 로고
    • Comparison between wavelet spectral features and conventional spectral features in detecting yellow rust for winter wheat
    • Zhang J., Yuan L., Pu R., Loraamm R.W., Yang G., Wang J. Comparison between wavelet spectral features and conventional spectral features in detecting yellow rust for winter wheat. Computers and Electronics in Agriculture 2014, 100:79-87.
    • (2014) Computers and Electronics in Agriculture , vol.100 , pp. 79-87
    • Zhang, J.1    Yuan, L.2    Pu, R.3    Loraamm, R.W.4    Yang, G.5    Wang, J.6
  • 69
    • 84932619439 scopus 로고    scopus 로고
    • Image-based field monitoring of Cercospora leaf spot in sugar beet by robust template matching and pattern recognition
    • Zhou R., Kaneko S., Tanaka F., Kayamori M., Shimizu M. Image-based field monitoring of Cercospora leaf spot in sugar beet by robust template matching and pattern recognition. Computers and Electronics in Agriculture 2015, 116:65-79.
    • (2015) Computers and Electronics in Agriculture , vol.116 , pp. 65-79
    • Zhou, R.1    Kaneko, S.2    Tanaka, F.3    Kayamori, M.4    Shimizu, M.5


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.