数字图像处理技术在农作物病虫草识别中的应用

[31] Detection of small pests on vegetable leaves using GLCM. Murakami S,Homma K,Koike T. American Society of Agricultural Engineers Paper Number　053136 .

[32] Color feature extraction by mans of discriminant analysis for wed segmentation. Jafari A,Mohtasebi S S,Jahromi H E,Omid M. American Society of Agricultural Engineers Paper Number　043059 .

[33] Crop/weed discrimination in perspective agronomic images. Ch.G‘ee,J.Bossu,G.Jones,F.Truchetet. Computers and Electronics in Agriculture . 2008

[34] Avision-basedmethodfor weedsidentificationthroughthe Bayesian decisiontheory. Tellaeche A,Burgos-Artizzu X P,Pajares G,et al. Pattern Recognition . 2008

[35] Large-scale investigation of weed seed identification by machine vision. Pablo.M Granitto,Pablo EVerdes,H.Alejandro.Ceccatto. Computers and Electronics in Agriculture . 2005

[36] Identification of citrus disease using color texture features and discriminant analysis. R. Pydipati,T. F. Burks, et al. Computers and Electronics in Agriculture . 2006

[37] statistical and neural network classifiers for citrus disease detection suing machine vision. R. Pydipati,T. F. Burks, et al. Transactions of the ASME .

[38] Backpropagation neural network design and evaluation for classifying weed species using color image texture. Burks,TF,Shearer,SA,Gates,RS,Donohue,KD. Transactions of the American Society of Agricultural Engineers . 2000

[39] Classification of Broadleaf and Grass weeds using Gabor wavelets and an artificial neural network. L.Tang,L.Tian,B.L.Steward. Transactions of the ASME . 2003

[40] Weed and crop discrimination using image analysis and artificial intelligence methods. Aitkenhead,MJ,Dalgetty,IA,Mullins,CE,McDonald,AJS,Strachan,NJC. Comput Electron Agri . 2003

[31] Detection of small pests on vegetable leaves using GLCM. Murakami S,Homma K,Koike T. American Society of Agricultural Engineers Paper Number　053136 .

[32] Color feature extraction by mans of discriminant analysis for wed segmentation. Jafari A,Mohtasebi S S,Jahromi H E,Omid M. American Society of Agricultural Engineers Paper Number　043059 .

[33] Crop/weed discrimination in perspective agronomic images. Ch.G‘ee,J.Bossu,G.Jones,F.Truchetet. Computers and Electronics in Agriculture . 2008

[34] Avision-basedmethodfor weedsidentificationthroughthe Bayesian decisiontheory. Tellaeche A,Burgos-Artizzu X P,Pajares G,et al. Pattern Recognition . 2008

[35] Large-scale investigation of weed seed identification by machine vision. Pablo.M Granitto,Pablo EVerdes,H.Alejandro.Ceccatto. Computers and Electronics in Agriculture . 2005

[36] Identification of citrus disease using color texture features and discriminant analysis. R. Pydipati,T. F. Burks, et al. Computers and Electronics in Agriculture . 2006

[37] statistical and neural network classifiers for citrus disease detection suing machine vision. R. Pydipati,T. F. Burks, et al. Transactions of the ASME .

[38] Backpropagation neural network design and evaluation for classifying weed species using color image texture. Burks,TF,Shearer,SA,Gates,RS,Donohue,KD. Transactions of the American Society of Agricultural Engineers . 2000

[39] Classification of Broadleaf and Grass weeds using Gabor wavelets and an artificial neural network. L.Tang,L.Tian,B.L.Steward. Transactions of the ASME . 2003

[40] Weed and crop discrimination using image analysis and artificial intelligence methods. Aitkenhead,MJ,Dalgetty,IA,Mullins,CE,McDonald,AJS,Strachan,NJC. Comput Electron Agri . 2003