欢迎来到海神之光博客之家✅博主简介热爱科研的Matlab仿真开发者修心和技术同步精进个人主页海神之光代码获取方式海神之光Matlab王者学习之路—代码获取方式⛳️座右铭行百里者半于九十。更多Matlab图像处理仿真内容点击①Matlab图像处理进阶版②付费专栏Matlab图像处理初级版⛳️关注CSDN海神之光更多资源等你来⛄一、模糊逻辑(Fuzzy Logic)简介理论知识参考模糊逻辑(Fuzzy Logic)⛄二、部分源代码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 EDITgui_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});endif nargout[varargout{1:nargout}] gui_mainfcn(gui_State, varargin{:});elsegui_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 LeafDiseaseGradingSystemGUIhandles.output hObject;% Update handles structureguidata(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 structurevarargout{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)I handles.I;% Creating color transformation from sRGB to Lab %cform makecform(‘srgb2lab’);lab_I applycform(I,cform);ab double(lab_I(:,:,2:3));nrows size(ab,1);ncols size(ab,2);ab reshape(ab,nrows*ncols,2);% No of clusters to be created with five iterations %nColors 5;[cluster_idx cluster_center] kmeans(ab,nColors,‘EmptyAction’,‘singleton’,‘distance’,‘sqEuclidean’,‘start’,[128,128;128,128;128,128;128,128;128,128]);pixel_labels reshape(cluster_idx,nrows,ncols);segmented_images cell(5);rgb_label repmat(pixel_labels,[1 1 3]);for k 1:nColorscolor I;color(rgb_label ~ k) 0;segmented_images{k} color;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);⛄三、运行结果⛄四、matlab版本及参考文献1 matlab版本2014a2 参考文献[1]张会孔,杨振霞,陈振东,刘汉舒.玉米粗缩病严重度分级标准的研究[J].植保技术与推广. 1998,(05)3 备注简介此部分摘自互联网仅供参考若侵权联系删除✅博主简介热爱科研的Matlab仿真开发者修心和技术同步精进Matlab项目合作可私信。个人主页海神之光代码获取方式海神之光Matlab王者学习之路—代码获取方式⛳️座右铭行百里者半于九十。更多Matlab仿真内容点击Matlab图像处理进阶版路径规划Matlab神经网络预测与分类Matlab优化求解Matlab语音处理Matlab信号处理Matlab车间调度Matlab