A list,

In the field of computer vision and image processing, the maximum inter-class variance method (OTSU), also known as OtsU method, is proposed by Japanese scholar Otsu in 1979, is an adaptive threshold segmentation method, reduce the gray image grade into a binary image. The algorithm assumes that the image is divided into two categories (in accordance with the bimodal histogram distribution, the two categories are called foreground/target pixels and background pixels respectively), and then calculates an optimal threshold that will divide the image into two categories to maximize the inter-class variance. Otsu is a one-dimensional representation of Fisher’s discrete judgment analysis.

2 methods





Ii. Source code

function varargout = experiment3(varargin)
% EXPERIMENT3 MATLAB code for experiment3.fig
%      EXPERIMENT3, by itself, creates a new EXPERIMENT3 or raises the existing
%      singleton*.
%
%      H = EXPERIMENT3 returns the handle to a new EXPERIMENT3 or the handle to
%      the existing singleton*.
%
%      EXPERIMENT3('CALLBACK',hObject,eventData,handles,...) calls the local
%      function named CALLBACK in EXPERIMENT3.M with the given input arguments.
%
%      EXPERIMENT3('Property','Value',...) creates a new EXPERIMENT3 or raises the
%      existing singleton*.  Starting from the left, property value pairs are
%      applied to the GUI before experiment3_OpeningFcn gets called.  An
%      unrecognized property name or invalid value makes property application
%      stop.  All inputs are passed to experiment3_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 experiment3
 
% Last Modified by GUIDE v2.5 31-May-2018 16:55:57
 
% Begin initialization code - DO NOT EDIT
gui_Singleton = 1;
gui_State = struct('gui_Name',       mfilename, ...
                   'gui_Singleton',  gui_Singleton, ...
                   'gui_OpeningFcn', @experiment3_OpeningFcn, ...
                   'gui_OutputFcn',  @experiment3_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 experiment3 is made visible.
function experiment3_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 experiment3 (see VARARGIN)
 
% Choose default command line output for experiment3
handles.output = hObject;
 
% Update handles structure
guidata(hObject, handles);
 
% UIWAIT makes experiment3 wait for user response (see UIRESUME)
% uiwait(handles.figure1);
 
 
% --- Outputs from this function are returned to the command line.
function varargout = experiment3_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;
 
 
 
function edit1_Callback(hObject, eventdata, handles)
% hObject    handle to edit1 (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 edit1 as text
%        str2double(get(hObject,'String')) returns contents of edit1 as a double
 
 
% --- Executes during object creation, after setting all properties.
function edit1_CreateFcn(hObject, eventdata, handles)
% hObject    handle to edit1 (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
 
% --- 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)
shiyan3 = rgb2gray(imread('shiyan3.bmp'));
size_filter_m = str2double(get(handles.edit1,'string'));
size_filter_n = str2double(get(handles.edit2,'string'));
if isnan(size_filter_m)
    size_filter_m = 3;
end
if isnan(size_filter_n)
    size_filter_n = 3;
end
shiyan3_filter = medfilt2(shiyan3,[size_filter_m,size_filter_n]);    %中值滤波
threshold = graythresh(shiyan3_filter); %用最大类间方差法找到阈值
shiyan3_seg = im2bw(shiyan3_filter,threshold);  %阈值分割
axes(handles.axes1);
imshow(shiyan3);
title('原图');
axes(handles.axes2);
imshow(shiyan3_filter);
title('中值滤波');
axes(handles.axes3);
imshow(shiyan3_seg);
title('类间方差阈值分割');
 
% --- 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)
shiyan3 = rgb2gray(imread('shiyan3.bmp'));
size_filter_m = str2double(get(handles.edit1,'string'));
size_filter_n = str2double(get(handles.edit2,'string'));
if isnan(size_filter_m)
    size_filter_m = 3;
end
if isnan(size_filter_n)
    size_filter_n = 3;
end
shiyan3_filter = medfilt2(shiyan3,[size_filter_m,size_filter_n]);    %中值滤波
threshold = graythresh(shiyan3_filter); %用最大类间方差法找到阈值
shiyan3_seg = im2bw(shiyan3_filter,threshold);  %阈值分割
axes(handles.axes1);
imshow(shiyan3);
title('原图');
axes(handles.axes2);
imshow(shiyan3_filter);
title('中值滤波');
axes(handles.axes3);
imshow(shiyan3_seg);
title('类间方差阈值分割');
 
se = strel('disk',1);  %结构元素
shiyan3_erode1 = imerode(shiyan3_seg,se);   %腐蚀
axes(handles.axes4);
imshow(shiyan3_erode1);
title('腐蚀: r=1');
 
se = strel('diamond',8);
shiyan3_erode2 = imerode(shiyan3_seg,se);
axes(handles.axes5);
imshow(shiyan3_erode2);
title('腐蚀: r=8');
 
se = strel('disk',8);
shiyan3_erode3 = imerode(shiyan3_seg,se);
axes(handles.axes6);
imshow(shiyan3_erode3);
title('腐蚀: r=8');
 
 
% --- 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)
shiyan3 = rgb2gray(imread('shiyan3.bmp'));
size_filter_m = str2double(get(handles.edit1,'string'));
size_filter_n = str2double(get(handles.edit2,'string'));
if isnan(size_filter_m)
    size_filter_m = 3;
end
if isnan(size_filter_n)
    size_filter_n = 3;
end
Copy the code

3. Operation results

Fourth, note

Complete code or simulation consulting to add QQ1575304183