【图像分割】基于matlab GUI多种阈值图像分割（带面板）【含Matlab源码 733期】

一、图像分割简介

理论知识参考：【基础教程】基于matlab图像处理图像分割【含Matlab源码 191期】

二、部分源代码

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 a new 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});
endif nargout[varargout{1:nargout}] = gui_mainfcn(gui_State, varargin{:});
elsegui_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'},'选择图片');
str=[pathname filename];
im=imread(str);
axes(handles.axes1);
imshow(im);
title('原始图像')
axes(handles.axes3);
if isrgb( im )im=rgb2gray(im);
end
hist_im=imhist(im); %计算直方图
bar(hist_im);%画直方图
title('原始图像灰度直方图')% --- 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;%通过迭代求最佳阈值while~dg=B>=T;%g=0或1Tn=0.5*(mean(B(g))+mean(B(~g)));%mean(A,2)是矩阵求各行的均值,%mean(A)表示求矩阵A的均值，默认的是求各列的均值if(abs(T-Tn)<0.1)d=1;endT=Tn;endaxes(handles.axes2);% 根据最佳阈值进行图像分割level=T/255;J=im2bw(B,level);imshow(J);title('使用基本全局阈值法');% --- 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);%otsuTh = graythresh(I);BW = im2bw(I,Th);axes(handles.axes2);imshow(BW);title('Otsu最佳阈值法');% --- 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-平均滤波时的窗口大小，可参考fspecial的用法%    C-0.03常量，需要根据经验选取合适的参数%  tm-开关变量，tm=1进行中值滤波，tm=0则进行均值滤波% bw-图像分割后输出的二值图像axes(handles.axes2);imshow(bw);title('自适应阈值');

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]赵勇,方宗德,庞辉,王侃伟.基于量子粒子群优化算法的最小交叉熵多阈值图像分割[J].计算机应用研究. 2008,(04)

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