1 模型
蔬菜病虫害的预警通常依靠植保专家知识来进行,较少采用数学建模方法来进行定量分析.为此,利用部分已知类别的训练样本抽取其关联规则作为监督信息,结合非监督学习的K-mean聚类算法,建立蔬菜黄曲条跳甲的预警模型.半监督学习算法既能发挥有监督学习准确率高的优点,又能充分地利用无监督学习的灵活性,具有一定的研究意义和实际意义.通过对广东省蔬菜黄曲条跳甲数据实验表明,半监督学习算法预警准确率比同条件下K-mean聚类算法的准确率高出24.31%.
2 部分代码
function?varargout?=?LeafDiseaseGradingSystemGUI(varargin)
% LeafDiseaseGradingSystemGUI MATLAB code for LeafDiseaseGradingSystemGUI.fig
% ? ? LeafDiseaseGradingSystemGUI, by itself, creates a new LeafDiseaseGradingSystemGUI or raises the existing
% ? ? singleton*.
%
% ? ? H = LeafDiseaseGradingSystemGUI returns the handle to a new LeafDiseaseGradingSystemGUI or the handle to
% ? ? the existing singleton*.
%
% ? ? LeafDiseaseGradingSystemGUI('CALLBACK',hObject,eventData,handles,...) calls the local
% ? ? function named CALLBACK in LeafDiseaseGradingSystemGUI.M with the given input arguments.
%
% ? ? LeafDiseaseGradingSystemGUI('Property','Value',...) creates a new LeafDiseaseGradingSystemGUI or raises the
% ? ? existing singleton*. Starting from the left, property value pairs are
% ? ? applied to the LeafDiseaseGradingSystemGUI before LeafDiseaseGradingSystemGUI_OpeningFcn gets called. An
% ? ? unrecognized property name or invalid value makes property application
% ? ? stop. All inputs are passed to LeafDiseaseGradingSystemGUI_OpeningFcn via varargin.
%
% ? ? *See LeafDiseaseGradingSystemGUI Options on GUIDE's Tools menu. Choose "LeafDiseaseGradingSystemGUI allows only one
% ? ? instance to run (singleton)".
%
% See also: GUIDE, GUIDATA, GUIHANDLES
% Edit the above text to modify the response to help LeafDiseaseGradingSystemGUI
% Last Modified by GUIDE v2.5 20-Jan-2015 14:49:28
% Begin initialization code - DO NOT EDIT
gui_Singleton?=?1;
gui_State?=?struct('gui_Name', ? ? ??mfilename,?...
? ? ? ? ? ? ? ? ??'gui_Singleton', ?gui_Singleton,?...
? ? ? ? ? ? ? ? ??'gui_OpeningFcn',?@LeafDiseaseGradingSystemGUI_OpeningFcn,?...
? ? ? ? ? ? ? ? ??'gui_OutputFcn', ?@LeafDiseaseGradingSystemGUI_OutputFcn,?...
? ? ? ? ? ? ? ? ??'gui_LayoutFcn', [] ,?...
? ? ? ? ? ? ? ? ??'gui_Callback', ? []);
if?nargin?&&?ischar(varargin{1})
? ?gui_State.gui_Callback?=?str2func(varargin{1});
end
if?nargout
? [varargout{1:nargout}] =?gui_mainfcn(gui_State,?varargin{:});
else
? ?gui_mainfcn(gui_State,?varargin{:});
end
% End initialization code - DO NOT EDIT
% --- Executes just before LeafDiseaseGradingSystemGUI is made visible.
function?LeafDiseaseGradingSystemGUI_OpeningFcn(hObject,?eventdata,?handles,?varargin)
% This function has no output args, see OutputFcn.
% hObject ? handle to figure
% eventdata reserved - to be defined in a future version of MATLAB
% handles ? structure with handles and user data (see GUIDATA)
% varargin ? command line arguments to LeafDiseaseGradingSystemGUI (see VARARGIN)
set(gcf,?'units','normalized','outerposition',[0?0?1?1]);
Disease_Grading?=?readfis('Disease_Grading.fis');
handles.Disease_Grading?=?Disease_Grading;
guidata(hObject,handles);
% Choose default command line output for LeafDiseaseGradingSystemGUI
handles.output?=?hObject;
% Update handles structure
guidata(hObject,?handles);
% UIWAIT makes LeafDiseaseGradingSystemGUI wait for user response (see UIRESUME)
% uiwait(handles.figure1);
% --- Outputs from this function are returned to the command line.
function?varargout?=?LeafDiseaseGradingSystemGUI_OutputFcn(hObject,?eventdata,?handles)?
% varargout cell array for returning output args (see VARARGOUT);
% hObject ? handle to figure
% eventdata reserved - to be defined in a future version of MATLAB
% handles ? structure with handles and user data (see GUIDATA)
% Get default command line output from handles structure
varargout{1} =?handles.output;
% --- Executes on button press in select_image.
function?select_image_Callback(hObject,?eventdata,?handles)
% hObject ? handle to select_image (see GCBO)
% eventdata reserved - to be defined in a future version of MATLAB
% handles ? structure with handles and user data (see GUIDATA)
? ? ? [File_Name,?Path_Name] =?uigetfile('PATHNAME');
? ? ??I?=?imread([Path_Name,File_Name]);
? ? ??imshow([Path_Name,File_Name],?'Parent',?handles.axes1);?title('Original Leaf Image',?'Parent',?handles.axes1);
? ? ??
? ? ??%# store queryname, version 1
? ? ??handles.I?=?I;
? ? ??guidata(hObject,handles);
? ? ??
% --- Executes on button press in segmentation.
function?segmentation_Callback(hObject,?eventdata,?handles)
% hObject ? handle to segmentation (see GCBO)
% eventdata reserved - to be defined in a future version of MATLAB
% handles ? structure with handles and user data (see GUIDATA)
end
% displaying different show_clusters objects %
I_cluster_1?=?segmented_images{1};
I_cluster_2?=?segmented_images{2};
I_cluster_3?=?segmented_images{3};
I_cluster_4?=?segmented_images{4};
I_cluster_5?=?segmented_images{5};
imshow(I_cluster_1,'Parent',?handles.axes2);?title('Cluster 1');
handles.I_cluster_1?=?I_cluster_1;
handles.I_cluster_2?=?I_cluster_2;
handles.I_cluster_3?=?I_cluster_3;
handles.I_cluster_4?=?I_cluster_4;
handles.I_cluster_5?=?I_cluster_5;
guidata(hObject,handles);
% --- Executes on button press in disease_grade.
function?disease_grade_Callback(hObject,?eventdata,?handles)
% hObject ? handle to disease_grade (see GCBO)
% eventdata reserved - to be defined in a future version of MATLAB
% handles ? structure with handles and user data (see GUIDATA)
Disease_Grading?=?handles.Disease_Grading;
white_pixels_I?=?handles.white_pixels_I?;
white_pixels_I_selected?=?handles.white_pixels_I_selected?;
percentage_infected?= (white_pixels_I_selected/white_pixels_I)*100;
grade?=?evalfis(percentage_infected,Disease_Grading);
figure();
plot(percentage_infected,grade,'g*');
legend('Percent - Grade of Disease');
title('Disease Grade Classification Using Fuzzy Logic');
xlabel('Percentage');
ylabel('Disease Grade');
% --- Executes on button press in binary_original.
function?binary_original_Callback(hObject,?eventdata,?handles)
% hObject ? handle to binary_original (see GCBO)
% eventdata reserved - to be defined in a future version of MATLAB
% handles ? structure with handles and user data (see GUIDATA)
I?=?handles.I;
BW_I?=?im2bw(I,0.17);
white_pixels_I?=?sum(BW_I(:)?==?1);
se?=?strel('disk',1);
closeBW?=?imclose(BW_I,se);
imshow(closeBW,'Parent',?handles.axes2);?title('Binary of Original Image');
handles.white_pixels_I?=?white_pixels_I;
guidata(hObject,handles);
% --- Executes on button press in binary_diseased.
function?binary_diseased_Callback(hObject,?eventdata,?handles)
% hObject ? handle to binary_diseased (see GCBO)
% eventdata reserved - to be defined in a future version of MATLAB
% handles ? structure with handles and user data (see GUIDATA)
I_selected?=?handles.I_slected?;
BW_I_selected?=?im2bw(I_selected,0.17);
white_pixels_I_selected?=?sum(BW_I_selected(:)?==?1);
se?=?strel('disk',5);
closeBW?=?imclose(BW_I_selected,se);
imshow(closeBW,'Parent',?handles.axes2);?title('Binary of Clustered Image');
handles.white_pixels_I_selected?=?white_pixels_I_selected;
guidata(hObject,handles);
% --- Executes on selection change in show_clusters.
function?show_clusters_Callback(hObject,?eventdata,?handles)
% hObject ? handle to show_clusters (see GCBO)
% eventdata reserved - to be defined in a future version of MATLAB
% handles ? structure with handles and user data (see GUIDATA)
% Hints: contents = cellstr(get(hObject,'String')) returns show_clusters contents as cell array
% ? ? ? contents{get(hObject,'Value')} returns selected item from show_clusters
I_cluster_1?=?handles.I_cluster_1?;
I_cluster_2?=?handles.I_cluster_2?;
I_cluster_3?=?handles.I_cluster_3?;
I_cluster_4?=?handles.I_cluster_4?;
I_cluster_5?=?handles.I_cluster_5?;
% Determine the selected data set.
str?=?get(hObject,?'String');
val?=?get(hObject,'Value');
% Set current data to the selected data set.
switch?str{val};
case?'Cluster 1'?% User selects peaks. ??
? ?imshow(I_cluster_1,'Parent',?handles.axes2);?title('Cluster 1');
? ?I_selected?=?I_cluster_1;
case?'Cluster 2'?% User selects membrane.
? ?imshow(I_cluster_2,'Parent',?handles.axes2);?title('Cluster 2');
? ?I_selected?=?I_cluster_2;
case?'Cluster 3'?% User selects sinc.
? ?imshow(I_cluster_3,'Parent',?handles.axes2);?title('Cluster 3');
? ?I_selected?=?I_cluster_3;
case?'Cluster 4'?% User selects sinc.
? ?imshow(I_cluster_4,'Parent',?handles.axes2);?title('Cluster 4');
? ?I_selected?=?I_cluster_4;
case?'Cluster 5'?% User selects sinc.
? ?imshow(I_cluster_5,'Parent',?handles.axes2);?title('Cluster 5');
? ?I_selected?=?I_cluster_5;
end
% Save the handles structure.
handles.I_slected?=?I_selected;
guidata(hObject,handles);
% --- Executes during object creation, after setting all properties.
function?show_clusters_CreateFcn(hObject,?eventdata,?handles)
% hObject ? handle to show_clusters (see GCBO)
% eventdata reserved - to be defined in a future version of MATLAB
% handles ? empty - handles not created until after all CreateFcns called
% Hint: popupmenu controls usually have a white background on Windows.
% ? ? ? See ISPC and COMPUTER.
if?ispc?&&?isequal(get(hObject,'BackgroundColor'),?get(0,'defaultUicontrolBackgroundColor'))
? ?set(hObject,'BackgroundColor','white');
end
%closing dilation
% --- Executes on button press in save_image.
function?save_image_Callback(hObject,?eventdata,?handles)
% hObject ? handle to save_image (see GCBO)
% eventdata reserved - to be defined in a future version of MATLAB
% handles ? structure with handles and user data (see GUIDATA)
axes2?=?handles.axes2;
axes1?=?handles.axes1;
h1=get(axes1,'Title');
h2=get(axes2,'Title');
figure();
subplot(1,2,1) ;?imshow(getimage(axes1));?title(h1.String);
subplot(1,2,2) ;?imshow(getimage(axes2));?title(h2.String);
3 仿真结果
4 参考文献
[1]王海超, 宗哲英, 张文霞, 殷晓飞, 王晓蓉, & 张海军等. (2019). 基于k均值聚类和环形结构提取算法的狭叶锦鸡儿木质部提取. 农业工程学报(1).?
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