MATLAB车牌识别-神经网络代码

function varargout = car_recognition(varargin) % CAR_RECOGNITION MATLAB code for car_recognition.fig % CAR_RECOGNITION, by itself, creates a new CAR_RECOGNITION or raises the existing % singleton*. % % H = CAR_RECOGNITION returns the handle to a new CAR_RECOGNITION or the handle to % the existing singleton*. % % CAR_RECOGNITION('CALLBACK',hObject,eventData,handles,...) calls the local % function named CALLBACK in CAR_RECOGNITION.M with the given input arguments. % % CAR_RECOGNITION('Property','Value',...) creates a new CAR_RECOGNITION or raises the % existing singleton*. Starting from the left, property value pairs are % applied to the GUI before car_recognition_OpeningFcn gets called. An % unrecognized property name or invalid value makes property application % stop. All inputs are passed to car_recognition_OpeningFcn via varargin. % % *See GUI Options on GUIDE's Tools menu. Choose "GUI allows only one % instance to run (singleton)". % % See also: GUIDE, GUIDATA, GUIHANDLES % Edit the above text to modify the response to help car_recognition % Last Modified by GUIDE v2.5 30-Dec-2017 21:01:04 % Begin initialization code - DO NOT EDIT gui_Singleton = 1; gui_State = struct('gui_Name', mfilename, ... 'gui_Singleton', gui_Singleton, ... 'gui_OpeningFcn', @car_recognition_OpeningFcn, ... 'gui_OutputFcn', @car_recognition_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 car_recognition is made visible. function car_recognition_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 car_recognition (see VARARGIN) % Choose default command line output for car_recognition handles.output = hObject; % Update handles structure guidata(hObject, handles); % UIWAIT makes car_recognition wait for user response (see UIRESUME) % uiwait(handles.figure1); % --- Outputs from this function are returned to the command line. function varargout = car_recognition_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 pushbutton1. function pushbutton1_Callback(hObject, eventdata, handles) % hObject handle to pushbutton1 (see GCBO) % eventdata reserved - to be defined in a future version of MATLAB % handles structure with handles and user data (see GUIDATA) global I [filename,pathname]=uigetfile('*.jpg','选择一张图片'); I=imread([pathname,filename]); axes(handles.axes1); imshow(I); % --- Executes on button press in pushbutton2. function pushbutton2_Callback(hObject, eventdata, handles) % hObject handle to pushbutton2 (see GCBO) % eventdata reserved - to be defined in a future version of MATLAB % handles structure with handles and user data (see GUIDATA) global I IGRAY=rgb2gray(I); %灰度直方图 [num]=grey_level_histogram(IGRAY); %均值化 [I_equal]=im_equal(num,IGRAY); %灰度拉伸 f=double(IGRAY); k1=min(min(f)); k2=max(max(f)); a=(k2-k1)/2; b=k2-80; c=k1-20; [s_grayequal]=gray_stretch(a,b,c,I_equal); [s_gray]=gray_stretch(a,b,c,IGRAY); %二值化 [J,thresh,I,Hi]=OTSU(s_grayequal); if sum(sum(J(:,1)))==size(J,1)*255 J=abs(255-J); end %边缘检测 I2=edge(J,'sobel',0.08,'both'); %腐蚀平滑图像 se=[1;1;1]; I3=imerode(I2,se);% 腐蚀Imerode(X,SE).其中X是待处理的图像，SE是结构元素对象 se = strel('line',11,90); fes=imdilate(I3,se); se=strel('rectangle',[8,8]);% 8X8的矩形 I4=imclose(fes,se);% 用8*8的矩形对图像进行闭运算(先膨胀后腐蚀)有平滑边界作用 I5=bwareaopen(I4,2000);% 从二进制图像中移除所有少于2000像素的连接对象，消失的是连续的白色像素数量少于2000的字符 [m,n]=size(I5); a=[]; b=[]; for i=1:m sum_x(i)=sum(I5(i,:)); if sum_x(i)~=0 a=[a i]; end end for i=1:n sum_y(i)=sum(I5(:,i)); if sum_y(i)~=0 b=[b i]; end end [J_gray,thresh,I,Hi]=OTSU(s_gray); %转换为黑底白字 if sum(sum(J_gray(:,3)))>=0.8*size(J_gray,1)*255 J_gray=abs(255-J_gray); end I6=J_gray(a(1,1):a(1,size(a,2)),b(1,1):b(1,size(b,2))); I6(:,1:2)=0; I6(:,size(I6,2))=0; I6(1:2,:)=0; I6(size(I6,1),:)=0; I6=bwareaopen(I6,60); imshow(I6); se=strel('rectangle',[8,8]); I7=imclose(I6,se);% 用8*8的矩形对图像进行闭运算(先膨胀后腐蚀)有平滑边界作用 %去除边框 JJ=I6; J=I7; [m,n]=size(JJ); JJ=bwareaopen(JJ,60); [JJ]=remove_border(J,JJ,m,n); %字符分割 [charsum]=division(JJ); % for i=0:6 % imwrite(charsum(:,1+16*i:16+16*i),[num2str(i+1),'.jpg']); % % end axes(handles.axes2); char1=charsum(:,1:16); char1=imresize(char1,[20,20],'nearest'); imshow(char1); axes(handles.axes3); char2=charsum(:,17:32); char2=imresize(char2,[20,20],'nearest'); imshow(char2); axes(handles.axes4); char3=charsum(:,33:48); char3=imresize(char3,[20,20],'nearest'); imshow(char3); axes(handles.axes5); char4=charsum(:,49:64); char4 = imresize(char4,[20,20],'nearest'); imshow(char4); axes(handles.axes6); char5=charsum(:,65:80); char5=imresize(char5,[20,20],'nearest'); imshow(char5); axes(handles.axes7); char6=charsum(:,81:96); char6=imresize(char6,[20,20],'nearest'); imshow(char6); axes(handles.axes8); char7=charsum(:,97:112); char7=imresize(char7,[20,20],'nearest'); imshow(char7); char1 = im2bw(char1); array_char1 = reshape(char1, [400, 1]); load('.\net_ch.mat'); test = sim(net_ch, array_char1); test = compet(test); [~, label] = max(test); [s1]=wordrec(label); char2 = im2bw(char2); array_char2 = reshape(char2, [400, 1]); load('.\net.mat'); test = sim(net, array_char2); test = compet(test); [~, label] = max(test); [s2]=numrec(label); char3 = im2bw(char3); array_char3 = reshape(char3, [400, 1]); load('.\net.mat'); test = sim(net, array_char3); test = compet(test); [~, label] = max(test); [s3]=numrec(label); char4 = im2bw(char4); array_char4 = reshape(char4, [400, 1]); load('.\net.mat'); test = sim(net, array_char4); test = compet(test); [~, label] = max(test); [s4]=numrec(label); char5 = im2bw(char5); array_char5 = reshape(char5, [400, 1]); load('.\net.mat'); test = sim(net, array_char5); test = compet(test); [~, label] = max(test); [s5]=numrec(label); char6 = im2bw(char6); array_char6 = reshape(char6, [400, 1]); load('.\net.mat'); test = sim(net, array_char6); test = compet(test); [~, label] = max(test); [s6]=numrec(label); char7 = im2bw(char7); array_char7 = reshape(char7, [400, 1]); load('.\net.mat'); test = sim(net, array_char7); test = compet(test); [~, label] = max(test); [s7]=numrec(label); s=char([s1,s2,s3,s4,s5,s6,s7]); h=msgbox(s,'识别结果'); %修改字体 ah=get(h,'CurrentAxes'); ch=get(ah,'Children'); set(ch,'FontSize',20); % 文本居中 th = findall(0, 'Tag','MessageBox' ); boxPosition = get(h,'position'); textPosition = get(th, 'position'); set(th, 'position', [boxPosition(3).*0.5 textPosition(2) textPosition(3)]); set(th, 'HorizontalAlignment', 'center'); set(h,'Position',[250 250 200 100]); % --- Executes during object creation, after setting all properties. function axes1_CreateFcn(hObject, eventdata, handles) % hObject handle to axes1 (see GCBO) % eventdata reserved - to be defined in a future version of MATLAB % handles empty - handles not created until after all CreateFcns called % Hint: place code in Openin