【毕业设计】基于Matlab的手写数字识别系统源码

function varargout = charGUI(varargin)
%窗体初始化代码
% Begin initialization code - DO NOT EDIT
gui_Singleton = 1;
gui_State = struct('gui_Name',       mfilename, ...
    'gui_Singleton',  gui_Singleton, ...
    'gui_OpeningFcn', @charGUI_OpeningFcn, ...
    'gui_OutputFcn',  @charGUI_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 charGUI is made visible.
function charGUI_OpeningFcn(hObject, eventdata, handles, varargin)
 
load data;
assignin('base','net',net);
handles.output = hObject;
set(gcf,'name','联系微信:matlab1998  ');
guidata(hObject, handles);
 
 
% --- Outputs from this function are returned to the command line.
function varargout = charGUI_OutputFcn(hObject, eventdata, handles)
 
 
% Get default command line output from handles structure
varargout{1} = handles.output;
 
 
% --- 装入图像.
function pbLoad_Callback(hObject, eventdata, handles)
[filename, pathname] = uigetfile({'*.bmp';'*.jpg';'*.gif';'*.*'}, '装入图像文件');
S = imread([pathname,filename]);
axes(handles.axes1);
imshow(S);
 
handles.S = S;
guidata(hObject, handles);
 
 
% --- 选择识别区域.
function pbSelect_Callback(hObject, eventdata, handles)
S = handles.S;
axes(handles.axes1);
img_crop = imcrop(S);
axes(handles.axes2);
imshow(img_crop);
 
handles.img_crop = img_crop;
guidata(hObject, handles);
 
 
 
% --- 图像预处理.
function pbPreprocess_Callback(hObject, eventdata, handles)
img_crop = handles.img_crop;
imgGray = rgb2gray(img_crop);
bw = im2bw(img_crop,graythresh(imgGray));
axes(handles.axes3);
imshow(bw);
bw2 = edu_imgcrop(bw);
axes(handles.axes4);
imshow(bw2);
handles.bw2 = bw2;
guidata(hObject, handles);
 
 
% --- 特征抽取.
function pbExtract_Callback(hObject, eventdata, handles)
 
 
msgbox('后续思路：微信:matlab1998')
return
 
% -字符识别.
function pbRecognize_Callback(hObject, eventdata, handles)
 
 
msgbox('后续思路：微信:matlab1998')
return
 
 
% --- Executes on button press in pbNN.
function pbNN_Callback(hObject, eventdata, handles)
 
 
 
 
function editNN_Callback(hObject, eventdata, handles)
 
function editNN_CreateFcn(hObject, eventdata, handles)
 
if ispc && isequal(get(hObject,'BackgroundColor'), get(0,'defaultUicontrolBackgroundColor'))
    set(hObject,'BackgroundColor','white');
end
 
 
function editResult_Callback(hObject, eventdata, handles)
 
function editResult_CreateFcn(hObject, eventdata, handles)
 
if ispc && isequal(get(hObject,'BackgroundColor'), get(0,'defaultUicontrolBackgroundColor'))
    set(hObject,'BackgroundColor','white');
end

%%训练神经网络
%% Read the image
I = imread('sample.bmp');
 
%% Image Preprocessing
img = edu_imgpreprocess(I);
for cnt = 1:50
    bw2 = edu_imgcrop(img{cnt});
    charvec = edu_imgresize(bw2);
    out(:,cnt) = charvec; 
end
 
%% Create Vectors for the components (objects)
P = out(:,1:40); 
T = [eye(10) eye(10) eye(10) eye(10)];
Ptest = out(:,41:50);
 
%% Creating and training of the Neural Network
net = edu_createnn(P,T);
 
%% Testing the Neural Network
[a,b]=max(sim(net,Ptest));
disp(b);