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









2 算法部分

二、部分源代码

% Project Title: Soil Detection & Classification


function varargout = SoilDetect_GUI(varargin)
% SOILDETECT_GUI MATLAB code for SoilDetect_GUI.fig
%      SOILDETECT_GUI, by itself, creates a new SOILDETECT_GUI or raises the existing
%      singleton*.
%
%      H = SOILDETECT_GUI returns the handle to a new SOILDETECT_GUI or the handle to
%      the existing singleton*.
%
%      SOILDETECT_GUI('CALLBACK',hObject,eventData,handles,...) calls the local
%      function named CALLBACK in SOILDETECT_GUI.M with the given input arguments.
%
%      SOILDETECT_GUI('Property','Value',...) creates a new SOILDETECT_GUI or raises the
%      existing singleton*.  Starting from the left, property value pairs are
%      applied to the GUI before SoilDetect_GUI_OpeningFcn gets called.  An
%      unrecognized property name or invalid value makes property application
%      stop.  All inputs are passed to SoilDetect_GUI_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 SoilDetect_GUI

% Last Modified by GUIDE v2.5 28-Aug-2021 14:31:16

% Begin initialization code - DO NOT EDIT
gui_Singleton = 1;
gui_State = struct('gui_Name',       mfilename, ...
                   'gui_Singleton',  gui_Singleton, ...
                   'gui_OpeningFcn', @SoilDetect_GUI_OpeningFcn, ...
                   'gui_OutputFcn',  @SoilDetect_GUI_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 SoilDetect_GUI is made visible.
function SoilDetect_GUI_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 SoilDetect_GUI (see VARARGIN)

% Choose default command line output for SoilDetect_GUI
handles.output = hObject;
handles.output = hObject;
ss = ones(300,400);
axes(handles.axes1);
imshow(ss);
axes(handles.axes2);
imshow(ss);
% Update handles structure
guidata(hObject, handles);

% UIWAIT makes SoilDetect_GUI wait for user response (see UIRESUME)
% uiwait(handles.figure1);


% --- Outputs from this function are returned to the command line.
function varargout = SoilDetect_GUI_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)
clc
[filename, pathname] = uigetfile({'*.*';'*.bmp';'*.jpg';'*.gif'}, 'Pick a Soil Image');
I = imread([pathname,filename]);
I = imresize(I,[256,256]);
I2 = imresize(I,[300,400]);
axes(handles.axes1);
imshow(I2);title('Query Image');
ss = ones(300,400);
axes(handles.axes2);
imshow(ss);
handles.ImgData1 = I;
guidata(hObject,handles);


% --- 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)
I3 = handles.ImgData1;
I4 = imadjust(I3,stretchlim(I3));
I5 = imresize(I4,[300,400]);
axes(handles.axes2);
imshow(I5);title(' Contrast Enhanced ');
handles.ImgData2 = I4;
%% Feature Extraction Part
   % queryimage = I4;
    %queryImage = imresize(queryImage, [256 256]);
    hsvHist = hsvHistogram(I4);
    autoCorrelogram = colorAutoCorrelogram(I4);
    color_moments = colorMoments(I4);
    % for gabor filters we need gary scale image
    img = double(rgb2gray(I4))/255;
    [meanAmplitude, msEnergy] = gaborWavelet(img, 4, 6); % 4 = number of scales, 6 = number of orientations
    wavelet_moments = waveletTransform(I4);
    % construct the queryImage feature vector
    Feature_Vector = [hsvHist autoCorrelogram color_moments meanAmplitude msEnergy wavelet_moments];
    whos Feature_Vector
    F1 = mean2(hsvHist(:));
    F2 = mean2(autoCorrelogram(:));
    F3 = mean2(color_moments(:));
    F4 = mean2(meanAmplitude(:));
    F5 = mean2(msEnergy(:));
    F6 = mean2(wavelet_moments(:));
    
    set(handles.edit3,'string',F1);
    set(handles.edit4,'string',F2);
    set(handles.edit5,'string',F3);
    set(handles.edit6,'string',F4);
    set(handles.edit7,'string',F5);
    set(handles.edit8,'string',F6);
    
    handles.ImgData3 = Feature_Vector;
guidata(hObject,handles);
%%
% --- Executes on button press in pushbutton3.
function pushbutton3_Callback(hObject, eventdata, handles)
% hObject    handle to pushbutton3 (see GCBO)
% eventdata  reserved - to be defined in a future version of MATLAB
% handles    structure with handles and user data (see GUIDATA)
load('TrainFeat_Soil.mat')

test = handles.ImgData3;
result = multisvm(TrainFeat,Train_Label,test);
disp(result);

if result == 1
    A1 = 'Clay';
    set(handles.edit1,'string',A1);
    helpdlg(' Clay ');
    disp(' Clay ');
elseif result == 2
    A2 = 'Clayey Peat';
    set(handles.edit1,'string',A2);
    helpdlg(' Clayey Peat ');
    disp('Clayey Peat');
elseif result == 3
    A3 = 'Clayey Sand';
    set(handles.edit1,'string',A3);
    helpdlg(' Clayey Sand ');
    disp(' Clayey Sand ');
elseif result == 4
    A4 = 'Humus Clay';
    set(handles.edit1,'string',A4);
    helpdlg(' Humus Clay ');
    disp(' Humus Clay ');
elseif result == 5
    A5 = 'Peat';
    set(handles.edit1,'string',A5);
    helpdlg(' Peat ');
    disp(' Peat ');
elseif result == 6
    A6 = 'Sandy Clay';
    set(handles.edit1,'string',A6);
    helpdlg(' Sandy Clay ');
    disp('Sandy Clay');
elseif result == 7
    A7 = 'Silty Sand';
    set(handles.edit1,'string',A7);
    helpdlg(' Silty Sand ');
    disp(' Silty Sand ');
end
guidata(hObject,handles);
% --- Executes on button press in pushbutton4.
function pushbutton4_Callback(hObject, eventdata, handles)
% hObject    handle to pushbutton4 (see GCBO)
% eventdata  reserved - to be defined in a future version of MATLAB
% handles    structure with handles and user data (see GUIDATA)
load('Accuracy_Data.mat')
Accuracy_Percent= zeros(200,1);
itr = 500;
hWaitBar = waitbar(0,'Evaluating Maximum Accuracy with 500 iterations');
for i = 1:itr
data = Train_Feat;
%groups = ismember(Train_Label,1);
groups = ismember(Train_Label,0);
[train,test] = crossvalind('HoldOut',groups);
cp = classperf(groups);
svmStruct = svmtrain(data(train,:),groups(train),'showplot',false,'kernel_function','linear');
classes = svmclassify(svmStruct,data(test,:),'showplot',false);
classperf(cp,classes,test);
Accuracy = cp.CorrectRate;
Accuracy_Percent(i) = Accuracy.*100;
sprintf('Accuracy of Linear Kernel is: %g%%',Accuracy_Percent(i))
waitbar(i/itr);
end

三、运行结果

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