【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');
elseset(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

% — 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

⛄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] 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)

3 备注
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