Image segmentation based on MATLAB GUI a variety of threshold image segmentation

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

% Last Modified by GUIDE v2. 5 05-Nov- 2017. 11:53:20

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

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

% Update handles structure
guidata(hObject, handles);

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


% --- Outputs from this function are returned to the command line.
function varargout = yuzhifenge_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)
global im;
[filename,pathname]=...
	uigetfile({'*.jpg';'*.bnp';'*.png'},'Select picture');
str=[pathname filename];
im=imread(str);
axes(handles.axes1);
imshow(im);
title('Original image')
axes(handles.axes3);
if isrgb( im )
    im=rgb2gray(im); end hist_im=imhist(im); % Calculate histogram bar(HIST_im); % Draw histogram title('Gray histogram of original image')

% --- 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)
close(gcf)

% --- Executes on button press in radiobutton1.
function radiobutton1_Callback(hObject, eventdata, handles)
% hObject    handle to radiobutton1 (see GCBO)
% eventdata  reserved - to be defined in a future version of MATLAB
% handles    structure with handles and user data (see GUIDATA)

% Hint: get(hObject,'Value') returns toggle state of radiobutton1
set(handles.radiobutton1,'value'.1);
set(handles.radiobutton2,'value'.0);
set(handles.radiobutton3,'value'.0);
set(handles.popupmenu1,'value'.1);
set(handles.popupmenu2,'value'.1);
global im;
        B=im;
        T=0.5* (double(min(B(:)))+double(max(B(:))));
        d=false; % Find the optimal threshold by iterationwhile~d g=B>=T; %g=0or1
         Tn=0.5*(mean(B(g))+mean(B(~g))); %mean(A,2), %mean(A), %mean(A), %mean(Aif(abs(T-Tn)<0.1)
         d=1;
         end
        T=Tn;
        end
        axes(handles.axes2); % Image segmentation according to the best threshold level=T/255;
        J=im2bw(B,level);
        imshow(J);
        title('Using the basic global threshold method');
        

% --- Executes on button press in radiobutton2.
function radiobutton2_Callback(hObject, eventdata, handles)
% hObject    handle to radiobutton2 (see GCBO)
% eventdata  reserved - to be defined in a future version of MATLAB
% handles    structure with handles and user data (see GUIDATA)

% Hint: get(hObject,'Value') returns toggle state of radiobutton2
set(handles.radiobutton1,'value'.0);
set(handles.radiobutton2,'value'.1);
set(handles.radiobutton3,'value'.0);
set(handles.popupmenu1,'value'.1);
set(handles.popupmenu2,'value'.1);
global im;
        I=im;
        I=im2double(I);
        %[width,height]=size(I);
        %otsu
        Th = graythresh(I);
        BW = im2bw(I,Th);
        axes(handles.axes2);
        imshow(BW);
        title('Otsu optimal threshold method ');
        

% --- Executes on button press in radiobutton3.
function radiobutton3_Callback(hObject, eventdata, handles)
% hObject    handle to radiobutton3 (see GCBO)
% eventdata  reserved - to be defined in a future version of MATLAB
% handles    structure with handles and user data (see GUIDATA)

% Hint: get(hObject,'Value') returns toggle state of radiobutton3
set(handles.radiobutton1,'value'.0);
set(handles.radiobutton2,'value'.0);
set(handles.radiobutton3,'value'.1);
set(handles.popupmenu1,'value'.1);
set(handles.popupmenu2,'value'.1);
global im;
        zi=im;
        bw=adaptivethreshold(zi,11.0.03.0); % ws=11- Average window size for filtering. Refer to the usage % C of fSpecial0.03Constant, according to experience to select the appropriate parameter % tm- switch variable, tm=1Perform median filtering, tm=0Then mean filtering % bw- binary image axes(handles. Axes2) output after image segmentation was performed; imshow(bw); title('Adaptive threshold');
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Version: 2014 a