【Matlab手写数字识别】SVM手写数字识别【含GUI源码 676期】

2022-01-17 15:32:44 阅读：188 来源： 互联网

标签：set 数字 gui axes write InputImage handles 手写识别

一、 SVM简介

支持向量机(Support Vector Machine)是Cortes和Vapnik于1995年首先提出的，它在解决小样本、非线性及高维模式识别中表现出许多特有的优势，并能够推广应用到函数拟合等其他机器学习问题中。
1 数学部分
1.1 二维空间
在这里插入图片描述

2 算法部分

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

在这里插入图片描述

四、matlab版本及参考文献

1 matlab版本
2014a

2 参考文献
[1] 蔡利梅.MATLAB图像处理——理论、算法与实例分析[M].清华大学出版社，2020.
[2]杨丹,赵海滨,龙哲.MATLAB图像处理实例详解[M].清华大学出版社，2013.
[3]周品.MATLAB图像处理与图形用户界面设计[M].清华大学出版社，2013.
[4]刘成龙.精通MATLAB图像处理[M].清华大学出版社，2015.

五、获取代码方式

Matlab王者助手CSDN名片

标签：set,数字,gui,axes,write,InputImage,handles,手写,识别
来源： https://blog.csdn.net/MLB_Q1564658423/article/details/122540806