一、简介

模型参考这里。

二、源代码

function varargout = Classification(varargin)
% Begin initialization code - DO NOT EDIT
gui_Singleton = 1;
gui_State = struct('gui_Name',       mfilename, ...
                   'gui_Singleton',  gui_Singleton, ...
                   'gui_OpeningFcn', @Classification_OpeningFcn, ...
                   'gui_OutputFcn',  @Classification_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 Classification is made visible.
function Classification_OpeningFcn(hObject, eventdata, handles, varargin)
handles.output = hObject;
% Update handles structure
guidata(hObject, handles);
​
%--------------------------------------------------------------------------
global flag
flag=0;
​
if exist('template.mat','file')~=0
    load template pattern;
else
    pattern(1,1).num=0;
    pattern(1,1).feature=[];
​
    pattern(1,2).num=0;
    pattern(1,2).feature=[];
​
    pattern(1,3).num=0;
    pattern(1,3).feature=[];
​
    pattern(1,4).num=0;
    pattern(1,4).feature=[];
​
    pattern(1,5).num=0;
    pattern(1,5).feature=[];
​
    pattern(1,6).num=0;
    pattern(1,6).feature=[];
​
    pattern(1,7).num=0;
    pattern(1,7).feature=[];
​
    pattern(1,8).num=0;
    pattern(1,8).feature=[];
​
    pattern(1,9).num=0;
    pattern(1,9).feature=[];
​
    pattern(1,10).num=0;
    pattern(1,10).feature=[];
    save template pattern;
end
%------------------------------------------------------------------------
​
% --- Outputs from this function are returned to the command line.
function varargout = Classification_OutputFcn(hObject, eventdata, handles) 
varargout{1} = handles.output;
​
​
%--------------------------------------------------------------------------
%手写板实现---按下左键开始画直线
function figure1_WindowButtonDownFcn(hObject, eventdata, handles)
%clc
​
global flag
global pos0  %
global x0 y0
​
pos0=get(handles.WritingAxes,'currentpoint');
x0=pos0(1,1);
y0=pos0(1,2);
if (pos0(1,1)>=0&pos0(1,1)<=100) && (pos0(1,2)>=0&pos0(1,2)<=100)  
    flag=1;
end
%--------------------------------------------------------------------------
​
​
​
%--------------------------------------------------------------------------
function figure1_WindowButtonMotionFcn(hObject, eventdata, handles)
%clc
%手写板实现---移动鼠标进行画线实现的程序
​
global flag
global pos0
global x0 y0
​
 pos=get(handles.WritingAxes,'currentpoint');   
 x=pos(1,1);
 y=pos(1,2);
 if flag && (pos(1,1)>=0&pos(1,1)<100) && (pos(1,2)>=0&pos(1,2)<100)  
      line(x,y, 'marker', '.','markerSize',18, 'LineStyle','-','LineWidth',2,'Color','Black');
      if x>x0
          stepX=0.1;
      else
          stepX=-0.1;
      end
      if y>y0
          stepY=0.1;
      else
          stepY=-0.1;
      end
      X=x0:stepX:x;      
                          
      if abs(x-x0)<0.01    
          Y=y0:stepY:y;     
      else
         Y=(y-y0)*(X-x0)/(x-x0)+y0;   
      end
      line(X ,Y, 'marker', '.','markerSize',18, 'LineStyle','-','LineWidth',2,'Color','Black');
      x0=x;
      y0=y;
      pos0=pos;
 else
      flag=0;
 end
 %-------------------------------------------------------------------------
 
​
 %-------------------------------------------------------------------------
function figure1_WindowButtonUpFcn(hObject, eventdata, handles)
%clc
%手写板实现程序---释放鼠标左键结束画线的程序
global flag
flag=0;
​
%global data
data=[];
Img=getframe(handles.WritingAxes);
imwrite(Img.cdata,'当前手写数字.bmp','bmp');
I=imread('当前手写数字.bmp');
I=rgb2gray(I);
I=im2bw(I);    
imwrite(I,'当前手写数字.bmp','bmp');
I=imread('当前手写数字.bmp');
data=GetFeature(I);
%--------------------------------------------------------------------------
function y=BayesLeastRisk(data)
clc;
load template pattern;
​
%将数字特征转化为0、1两个数值表示
for i=1:10
    for j=1:25
        for k=1:pattern(1,i).num
            if pattern(1,i).feature(j,k)>0.1
               pattern(1,i).feature(j,k)=1;
            else
                pattern(1,i).feature(j,k)=0;
            end
        end
    end
end
​
[pc_template,pc_data]=pcapro(data); %主成分分析 
temp=0;
for i=1:10
    pattern(1,i).feature=pc_template(:,temp+1:temp+pattern(1,i).num);
    temp=temp+pattern(1,i).num;
end
​
​
%求协方差矩阵、协方差矩阵的逆矩阵、协方差矩阵的行列式
s_cov=[];
s_inv=[];
s_det=[];
​
for i=1:10
    s_cov(i).data=cov(pattern(1,i).feature');
    s_inv(i).data=inv(s_cov(i).data);
    s_det(i)=det(s_cov(i).data);
end

三、运行结果

​ ​ ​ ​ ​ ​ ​ ​ ​

##

四、参考文献

[1]周佳敏. 基于贝叶斯网络的手写数字识别的研究与应用[J]. 科技视界, 2013(08):27-27.

博主简介：擅长智能优化算法、神经网络预测、信号处理、元胞自动机、图像处理、路径规划、无人机等多种领域的Matlab仿真，相关matlab代码问题可私信交流。

部分理论引用网络文献，若有侵权联系博主删除。

一、基于支持向量机SVM实现手写数字识别

​ 模型参考这里。​ ​ ​

二、源代码

function varargout = DigitClassifyUI(varargin)
​
%
​
​
% DIGITCLASSIFYUI MATLAB code for DigitClassifyUI.fig
​
% DIGITCLASSIFYUI, by itself, creates a new DIGITCLASSIFYUI or raises the existing
​
% singleton*.
​
%
​
% H = DIGITCLASSIFYUI returns the handle to a new DIGITCLASSIFYUI or the handle to
​
% the existing singleton*.
​
%
​
% DIGITCLASSIFYUI('CALLBACK',hObject,eventData,handles,...) calls the local
​
% function named CALLBACK in DIGITCLASSIFYUI.M with the given input arguments.
​
%
​
% DIGITCLASSIFYUI('Property','Value',...) creates a new DIGITCLASSIFYUI or raises the
​
% existing singleton*. Starting from the left, property value pairs are
​
% applied to the GUI before DigitClassifyUI_OpeningFcn gets called. An
​
% unrecognized property name or invalid value makes property application
​
% stop. All inputs are passed to DigitClassifyUI_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 DigitClassifyUI
​
​
% Last Modified by GUIDE v2.5 10-Feb-2021 18:44:08
​
​
% Begin initialization code - DO NOT EDIT
​
gui_Singleton = 1;
​
gui_State = struct('gui_Name', mfilename, ...
​
'gui_Singleton', gui_Singleton, ...
​
'gui_OpeningFcn', @DigitClassifyUI_OpeningFcn, ...
​
'gui_OutputFcn', @DigitClassifyUI_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 DigitClassifyUI is made visible.
​
function DigitClassifyUI_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 DigitClassifyUI (see VARARGIN)
​
​
% Choose default command line output for DigitClassifyUI
​
handles.output = hObject;
​
​
% Update handles structure
​
guidata(hObject, handles);
​
​
% UIWAIT makes DigitClassifyUI wait for user response (see UIRESUME)
​
% uiwait(handles.figure1);
​
global FigHandle AxesHandle RectHandle;
​
FigHandle = handles.output;
​
AxesHandle = handles.axes_write;
​
MouseDraw();
​
axis(handles.axes_write,[1 400 1 400]); % 设定图轴范围
​
RectHandle = rectangle(handles.axes_write,'Position',[80,66,240,268],'LineStyle','--','EdgeColor','#a9a9a9');
​
​
% --- Outputs from this function are returned to the command line.
​
function varargout = DigitClassifyUI_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)
​
​
​
% --- Executes on button press in pushbutton_loadImage.
​
function pushbutton_loadImage_Callback(hObject, eventdata, handles)
​
% hObject handle to pushbutton_loadImage (see GCBO)
​
% eventdata reserved - to be defined in a future version of MATLAB
​
% handles structure with handles and user data (see GUIDATA)
​
global RectHandle;
​
cla(handles.axes_write, 'reset')
​
set(handles.axes_write, 'Visible','off');
​
set(handles.output, 'Pointer', 'arrow');
​
axis(handles.axes_write,[1 400 1 400]); % 设定图轴范围
​
RectHandle = rectangle(handles.axes_write,'Position',[80,66,240,268],'LineStyle','--','EdgeColor','#a9a9a9');
​
​
% 弹出文件选择框，选择一张图片
​
[file,path] = uigetfile({'*.jpg;*.jpeg;*.png;*.bmp;*.tif',...
​
'图片文件 (*.jpg,*.jpeg,*.png,*.bmp,*.tif)'},'选择一张图片');
​
if isequal(file,0) % 若文件不存在
​
set(handles.edit_imagePath, 'String','请选择一张图片');
​
else
​
fileName= fullfile(path, file); % 选择的图片绝对路径
​
set(handles.edit_imagePath, 'String', fileName); % 显示选择的图片路径
​
InputImage = imread(fileName);
​
image(handles.axes_raw, InputImage);
​
set(handles.axes_raw, 'Visible','off');
​
​
set(gcf, 'Pointer', 'arrow');
​
set(gcf, 'WindowButtonMotionFcn', '')
​
set(gcf, 'WindowButtonUpFcn', '')
​
​
​
% 开始执行预处理
​
if numel(size(InputImage))==3
​
InputImage = rgb2gray(InputImage); % 灰度化图片
​
axes(handles.axes_gray);
​
imshow(InputImage);
​
else
​
axes(handles.axes_gray);
​
imshow(InputImage);
​
end
​
% 二值化
​
InputImage = imbinarize(InputImage);
​
axes(handles.axes_binary);
​
imshow(InputImage);
​
​
% 特征提取
​
InputImage = imresize(InputImage, [28, 28]);
​
cellSize = [4 4];
​
[~, vis4x4] = extractHOGFeatures(InputImage,'CellSize',[4 4]);
​
axes(handles.axes_features);
​
plot(vis4x4);
​
​
load('trainedSvmModel.mat','classifier');
​
features(1, :) = extractHOGFeatures(InputImage,'CellSize',cellSize);
​
predictedLabel = predict(classifier, features);
​
str = string(predictedLabel);
​
set(handles.text_result, 'String', str);
​
end
​
axes(handles.axes_write);
​
MouseDraw();
​
% set(gcf, 'WindowButtonDownFcn', '');
​
​
​
​
% --- Executes on button press in pushbutton_load.
​
function pushbutton_load_Callback(hObject, eventdata, handles)
​
% hObject handle to pushbutton_load (see GCBO)
​
% eventdata reserved - to be defined in a future version of MATLAB
​
% handles structure with handles and user data (see GUIDATA)
​
global RectHandle;
​
axis(handles.axes_write,[1 400 1 400]); % 设定图轴范围
​
set(handles.edit_imagePath, 'String','请选择一张图片');
​
delete(RectHandle);
​
h=getframe(handles.axes_write);
​
imwrite(h.cdata,'writedImage.jpg');
​
​
InputImage = imread('writedImage.jpg');
​
% InputImage = cat(3, InputImage,InputImage,InputImage);
​
image(handles.axes_raw,InputImage);
​
set(handles.axes_raw, 'Visible','off');
​
axis(handles.axes_write,[1 400 1 400]); % 设定图轴范围
​
RectHandle = rectangle(handles.axes_write,'Position',[80,66,240,268],'LineStyle','--','EdgeColor','#a9a9a9');
​
global FigHandle
​
set(FigHandle, 'Pointer', 'arrow');
​
set(FigHandle, 'WindowButtonMotionFcn', '')
​
set(FigHandle, 'WindowButtonUpFcn', '')
​
set(FigHandle, 'WindowButtonDownFcn', '');
​
​
% 开始执行预处理
​
if numel(size(InputImage))==3
​
InputImage = rgb2gray(InputImage); % 灰度化图片
​
axes(handles.axes_gray);
​
imshow(InputImage);
​
else
​
axes(handles.axes_gray);
​
imshow(InputImage);
​
end
​
% 二值化
​
InputImage = imbinarize(InputImage);
​
axes(handles.axes_binary);
​
imshow(InputImage);
​
​
% 特征提取
​
InputImage = imresize(InputImage, [28, 28]);
​
cellSize = [4 4];
​
[~, vis4x4] = extractHOGFeatures(InputImage,'CellSize',[4 4]);
​
axes(handles.axes_features);
​
plot(vis4x4);
​
​
load('trainedSvmModel.mat','classifier');
​
features(1, :) = extractHOGFeatures(InputImage,'CellSize',cellSize);
​
predictedLabel = predict(classifier, features);
​
str = string(predictedLabel);
​
set(handles.text_result, 'String', str);
​
MouseDraw();
​
​
% --- Executes on button press in pushbutton_clear.
​
function pushbutton_clear_Callback(hObject, eventdata, handles)
​
% hObject handle to pushbutton_clear (see GCBO)
​
% eventdata reserved - to be defined in a future version of MATLAB
​
% handles structure with handles and user data (see GUIDATA)
​
global RectHandle;
​
global FigHandle
​
set(FigHandle, 'Pointer', 'arrow');
​
set(FigHandle, 'WindowButtonMotionFcn', '')
​
set(FigHandle, 'WindowButtonUpFcn', '')
​
set(FigHandle, 'WindowButtonDownFcn', '');
​
set(handles.edit_imagePath, 'String','请选择一张图片');
​
set(handles.text_result, 'String', 'None');
​
cla(handles.axes_write, 'reset')
​
set(handles.axes_write, 'Visible','off');
​
cla(handles.axes_raw, 'reset')
​
set(handles.axes_raw, 'Visible','off');
​
cla(handles.axes_gray, 'reset')
​
set(handles.axes_gray, 'Visible','off');
​
cla(handles.axes_binary, 'reset')
​
set(handles.axes_binary, 'Visible','off');
​
cla(handles.axes_features, 'reset')
​
set(handles.axes_features, 'Visible','off');
​
set(handles.output, 'Pointer', 'arrow');
​
​
axis(handles.axes_write,[1 400 1 400]); % 设定图轴范围
​
RectHandle = rectangle(handles.axes_write,'Position',[80,66,240,268],'LineStyle','--','EdgeColor','#a9a9a9');
​
MouseDraw();

三、运行结果

4 参考文献

[1]徐铭杰. 基于支持向量机的字符识别系统的研究与实现[D]. 浙江工业大学.

博主简介：擅长智能优化算法、神经网络预测、信号处理、元胞自动机、图像处理、路径规划、无人机等多种领域的Matlab仿真，相关matlab代码问题可私信交流。

部分理论引用网络文献，若有侵权联系博主删除。