【人脸识别】基于matlab GUI LPP人脸特征提取【含Matlab源码 1491期】

一、简介

理论知识参考文献：基于局部特征提取人脸识别方法优化研究

二、部分源代码

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

% Last Modified by GUIDE v2.5 25-May-2021 21:40:39

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

% Choose default command line output for spectacles_lpp_classification
handles.output = hObject;

% Update handles structure
guidata(hObject, handles);

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


% --- Outputs from this function are returned to the command line.
function varargout = spectacles_lpp_classification_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 selection change in lstPositive.
function lstPositive_Callback(hObject, eventdata, handles)
% hObject    handle to lstPositive (see GCBO)
% eventdata  reserved - to be defined in a future version of MATLAB
% handles    structure with handles and user data (see GUIDATA)

% Hints: contents = cellstr(get(hObject,'String')) returns lstPositive contents as cell array
%        contents{get(hObject,'Value')} returns selected item from lstPositive
displayCurrentItem(hObject,handles)

% --- Executes during object creation, after setting all properties.
function lstPositive_CreateFcn(hObject, eventdata, handles)
% hObject    handle to lstPositive (see GCBO)
% eventdata  reserved - to be defined in a future version of MATLAB
% handles    empty - handles not created until after all CreateFcns called

% Hint: listbox controls usually have a white background on Windows.
%       See ISPC and COMPUTER.
if ispc && isequal(get(hObject,'BackgroundColor'), get(0,'defaultUicontrolBackgroundColor'))
    set(hObject,'BackgroundColor','white');
end

function decision = getDecision(current_image)
global projected_data Positive_mean sgn;

for i = 1:length(current_image)
    decision(i) = (sgn(Positive_mean(1),Positive_mean(2))* ...
        sgn(projected_data(current_image(i),1),projected_data( ...
        current_image(i),2))>0);
end

function displayCurrentItem(hObject,handles)
global dat_a_ height width projected_data;

contents = cellstr(get(hObject,'String'));
current_image = str2double(contents{get(hObject,'Value')});
datalet = dat_a_(current_image,1:end-1);
img = uint8(reshape(datalet,height,width));
imshow(img,'Parent',handles.plotArea2);

if (~isempty(projected_data))
    h = get(handles.plotArea1,'Children');
    allAvailableTypes = get(h,'type');
    [tf,loc]=ismember('text',allAvailableTypes);
    if(~tf)
        text(projected_data(current_image,1), ...
            projected_data(current_image,2), num2str(current_image), ...
            'Parent',handles.plotArea1,'FontWeight','bold');
    else
        set(h(loc),'Position',[projected_data(current_image,1), ...
            projected_data(current_image,2)],'String', ...
            num2str(current_image));
    end
    
    if(getDecision(current_image))
        set(handles.result,'String','With Spectacles');
    else
        set(handles.result,'String','Without Spectacles');
    end
end

% --- Executes on selection change in lstTest.
function lstTest_Callback(hObject, eventdata, handles)
% hObject    handle to lstTest (see GCBO)
% eventdata  reserved - to be defined in a future version of MATLAB
% handles    structure with handles and user data (see GUIDATA)

% Hints: contents = cellstr(get(hObject,'String')) returns lstTest contents as cell array
%        contents{get(hObject,'Value')} returns selected item from lstTest
displayCurrentItem(hObject,handles)


% --- Executes during object creation, after setting all properties.
function lstTest_CreateFcn(hObject, eventdata, handles)
% hObject    handle to lstTest (see GCBO)
% eventdata  reserved - to be defined in a future version of MATLAB
% handles    empty - handles not created until after all CreateFcns called

% Hint: listbox controls usually have a white background on Windows.
%       See ISPC and COMPUTER.
if ispc && isequal(get(hObject,'BackgroundColor'), get(0,'defaultUicontrolBackgroundColor'))
    set(hObject,'BackgroundColor','white');
end


% --- 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 dat_a_ Name_Database height width projected_data;

dat_a_=[];
Name_Database=[];
height=[];
width=[];
projected_data=[];

% Loading the database file
filename = uigetfile('*.mat', 'Select database file');
load(filename);
dat_a_ = data;

%Check if it is loaded correctly
if exist('Database_name','var')
    Name_Database = Database_name;
    
    % Get the number of elements loaded
    m = size(dat_a_,1);
    pos_count = sum(dat_a_(:,end));
    neg_count = m - pos_count;
    
    % Show a notification of how many elements are loaded
    set(handles.txtloadPrompt,'String',sprintf('%d items loaded',m));
    
    % Calculating amount of training data
    % The rule of selection: See whether the positive or the
    % negative samples are fewer in amount. Take half of the data from the
    % fewer class and an equal number of data from the other class. So,
    % the total number of training data = 2 * (1/2) * min(amount of data in
    % class with sunglass, amount of data in class without sunglass)
    training_size = min(pos_count,neg_count);
    test_size = m - training_size;
    set(handles.txtSizeTraining,'String',num2str(training_size));
    set(handles.txtSizeTesting,'String',num2str(test_size));
else
    msgbox('The database could not be loaded');
    
end




function txtSizeTraining_Callback(hObject, eventdata, handles)
% hObject    handle to txtSizeTraining (see GCBO)
% eventdata  reserved - to be defined in a future version of MATLAB
% handles    structure with handles and user data (see GUIDATA)

% Hints: get(hObject,'String') returns contents of txtSizeTraining as text
%        str2double(get(hObject,'String')) returns contents of txtSizeTraining as a double
global dat_a_;
m = size(dat_a_,1);
m_n = str2double(get(hObject, 'String'));
set(handles.txtSizeTesting,'String',m - m_n);


% --- Executes during object creation, after setting all properties.
function txtSizeTraining_CreateFcn(hObject, eventdata, handles)
% hObject    handle to txtSizeTraining (see GCBO)
% eventdata  reserved - to be defined in a future version of MATLAB
% handles    empty - handles not created until after all CreateFcns called

% Hint: edit controls usually have a white background on Windows.
%       See ISPC and COMPUTER.
if ispc && isequal(get(hObject,'BackgroundColor'), get(0,'defaultUicontrolBackgroundColor'))
    set(hObject,'BackgroundColor','white');
end



function txtSizeTesting_Callback(hObject, eventdata, handles)
% hObject    handle to txtSizeTesting (see GCBO)
% eventdata  reserved - to be defined in a future version of MATLAB
% handles    structure with handles and user data (see GUIDATA)

% Hints: get(hObject,'String') returns contents of txtSizeTesting as text
%        str2double(get(hObject,'String')) returns contents of txtSizeTesting as a double


% --- Executes during object creation, after setting all properties.
function txtSizeTesting_CreateFcn(hObject, eventdata, handles)
% hObject    handle to txtSizeTesting (see GCBO)
% eventdata  reserved - to be defined in a future version of MATLAB
% handles    empty - handles not created until after all CreateFcns called

% Hint: edit controls usually have a white background on Windows.
%       See ISPC and COMPUTER.
if ispc && isequal(get(hObject,'BackgroundColor'), get(0,'defaultUicontrolBackgroundColor'))
    set(hObject,'BackgroundColor','white');
end


  

 

  
1
  
2
  
3
  
4
  
5
  
6
  
7
  
8
  
9
  
10
  
11
  
12
  
13
  
14
  
15
  
16
  
17
  
18
  
19
  
20
  
21
  
22
  
23
  
24
  
25
  
26
  
27
  
28
  
29
  
30
  
31
  
32
  
33
  
34
  
35
  
36
  
37
  
38
  
39
  
40
  
41
  
42
  
43
  
44
  
45
  
46
  
47
  
48
  
49
  
50
  
51
  
52
  
53
  
54
  
55
  
56
  
57
  
58
  
59
  
60
  
61
  
62
  
63
  
64
  
65
  
66
  
67
  
68
  
69
  
70
  
71
  
72
  
73
  
74
  
75
  
76
  
77
  
78
  
79
  
80
  
81
  
82
  
83
  
84
  
85
  
86
  
87
  
88
  
89
  
90
  
91
  
92
  
93
  
94
  
95
  
96
  
97
  
98
  
99
  
100
  
101
  
102
  
103
  
104
  
105
  
106
  
107
  
108
  
109
  
110
  
111
  
112
  
113
  
114
  
115
  
116
  
117
  
118
  
119
  
120
  
121
  
122
  
123
  
124
  
125
  
126
  
127
  
128
  
129
  
130
  
131
  
132
  
133
  
134
  
135
  
136
  
137
  
138
  
139
  
140
  
141
  
142
  
143
  
144
  
145
  
146
  
147
  
148
  
149
  
150
  
151
  
152
  
153
  
154
  
155
  
156
  
157
  
158
  
159
  
160
  
161
  
162
  
163
  
164
  
165
  
166
  
167
  
168
  
169
  
170
  
171
  
172
  
173
  
174
  
175
  
176
  
177
  
178
  
179
  
180
  
181
  
182
  
183
  
184
  
185
  
186
  
187
  
188
  
189
  
190
  
191
  
192
  
193
  
194
  
195
  
196
  
197
  
198
  
199
  
200
  
201
  
202
  
203
  
204
  
205
  
206
  
207
  
208
  
209
  
210
  
211
  
212
  
213
  
214
  
215
  
216
  
217
  
218
  
219
  
220
  
221
  
222
  
223
  
224
  
225
  
226
  
227
  
228
  
229
  
230
  
231
  
232
  
233
  
234
  
235
  
236
  
237
  
238
  
239
  
240
  
241
  
242
  
243
  
244
  
245
  
246
  
247
  
248
  
249
  
250
  
251
  
252
  
253
  
254
  
255
  
256
 

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.
[5]李奇杰,杨洪臣.基于局部特征提取人脸识别方法优化研究[J].金融科技时代. 2021,29(04)

文章来源: qq912100926.blog.csdn.net，作者：海神之光，版权归原作者所有，如需转载，请联系作者。

原文链接：qq912100926.blog.csdn.net/article/details/113694525