【水果识别】基于matlab GUI形态学水果大小识别【含Matlab源码 920期】

编程入门行业动态更新时间:2024-10-27 06:25:28

⛄一、形态学缺陷检测简介

1 图像分析及预处理
拍摄图像会产生随机的扰动，图像有一定的噪声，为消除掉图像中的无关信息，对图像进行预处理。

1.1 灰度化
为降低运算量，需要将拍摄的三通道的RGB图像转化为单通道的灰度图像。采用加权平均法的灰度化方法，其中心理学灰度公式根据人眼对RGB三色的敏感程度选择不同的权重：

式（1）中，R、G、B分别为RGB三通道灰度值，灰度化结果如图1 (a）所示。

1.2 平滑处理
为了尽可能避免将背景当作缺陷，需要对图像进行平滑处理，这样虽然会使缺陷的边界模糊，但是有利于减少背景的干扰。注意所采用的去噪处理为均值滤波，均值滤波公式为：

式（2）中，m、n分别为所选择的滤波核的长和宽，Sxy是以(x,y)为中心的滤波核对应像素的位置集合，平滑处理结果如图1 (b）所示。均值滤波的缺点是会使一些细节如边缘等信息丢失，因此在找到种子点后，对没有经过平滑处理的图像进行区域生长，找到缺陷边界。

2 算法原理
2.1 阈值分割
阈值分割是图像分割中最简单、基础的方法，性能比较稳定，计算量较小，运算速度快；它主要有全局阈值分割、局部阈值分割、自适应阈值分割等方法。阈值算法基于阈值T，将像素灰度值大于阈值T和小于阈值T的部分分别叫做前景和背景。变换函数表达式：

图1 均值滤波处理

式（3）中，T为阈值，g (x,y)为原图像像素点(x,y)的灰度值，f (x,y)为分割后图像像素点(x,y)的灰度值，阈值分割结果如图2所示。

图2 阈值分割结果

2.2 形态学开运算降噪
数学形态学简称形态学，其处理方式为领域运算，即把领域结构元素与图像对应位置像素进行逻辑运算，这种运算的影响因素主要有结构元素大小、形状和逻辑运算的规则。形态学操作主要有膨胀、腐蚀、梯度运算、礼帽运算、黑帽运算、开运算和闭运算等，但其基础为腐蚀和膨胀，利用膨胀和腐蚀就能完成不同形式的运算。

腐蚀运算能消除轮廓边界点，使边界向内缩小，主要用于细化二值图像目标轮廓、去除噪声等。

式（4）中，A为原图像，B为结构元素。首先给结构元素B定义一个原点，当结构元素B的原点移动到图像A的(x,y)上时，如果结构元素B上等于1的像素点对应图像A也等于1，则将图像A的(x,y)的灰度值置为1，否则置为0，腐蚀示意图如图3所示。

图3 腐蚀示意图
膨胀运算则与腐蚀运算相反，使边界向外扩张，主要用于填补图像分割后的空白，使相近的不相连的轮廓相连。其公式为：

式（5）中，A为原图像，B为结构元素。首先给结构元素B定义一个原点，当结构元素B的原点移动到图像A的(x,y)上时，如果结构元素B上等于1的像素点对应图像A中至少有一个等于1，则将图像A的(x,y)的灰度值置为1，否则置为0。

先进行腐蚀操作，然后在腐蚀的基础上进行膨胀操作，主要用于去噪和计数等。其公式为：

式（6）中，A为原图像，B、C为结构元素。开运算效果如图4所示，图5为开运算处理的结果。

图4 开运算效果
2.3 区域生长法
区域生长的思想就是把领域（四领域、八领域等）相同的化为一个区域。首先需要一个种子点作为生长的开始，然后将种子点领域内满足相似准则要求的像素点合并到种子的区域，将这个区域的像素做为种子点，继续进行生长，直到没有符合要求的点，生长结束，所有种子点像素作为生长的区域。分割的好坏由初始种子点和相似准则决定。

图5 形态学开运算结果
2.3.1 种子点选择与检测
经过阈值分割和形态学处理后，将二值图像各轮廓中心作为待定种子点。如果选择的种子点位于缺陷的绝对区域，那么种子点总有一个方向各像素的深度值呈现高-低-高的形态。设计检测模板如图6所示，计算出种子点在0°、45°、90°、135°方向上的深度变化，判断其变化是否呈高低高形态。

图6 检测模板
种子点左右两侧r个像素的灰度平均值分别为：

各方向的灰度变化为：

深度形Si态变化判定：

式（10）中，I (u)为检测模板中第u个像素的灰度值，w=1,2,3,4，分别代表0°，45°，90°，135°方向，mwm为w方向两侧的最小灰度值，T1为形态变化阈值。如果种子点不满足深度形态变化判定，则去除该待定种子点。

2.3.2 生长过程
区域生长的具体流程如下：
(1）将种子点坐标放入种子点集seeds。
(2）顶出种子点集中的一个种子点，对种子点八邻域的像素点进行相似准则判断；满足相似准则条件的点，视为种子点放入种子点集seeds。
(3）将顶出的种子点存入种子集S。
(4）如果种子点集内没有元素，则跳到步骤（4）；如果种子点集中还有元素，则跳到步骤（2）。
(5）生成一张和输入图像长宽一致，像素值全为0的图像I。
(6）将图像I中对应种子集S坐标的像素值置为255，得到分割图像I’。
其中生长的相似准则为：

式（11）中，gray (seed)为当轮种子点的灰度值，gray (8＿n)为其八邻域各点的像素值，Thresh为设置的阈值。区域生长结果如图7所示。

图7 区域生长结果
3 实验过程
图像分割就是按照预先设定的规则，将图像分割为有意义的前景和背景的过程。区域生长是一个分割效果比较好的算法，但前提是需要找到适合的种子点。单一的分割算法就容易遇到这种不足的情况，结合使用形态学和阈值分割的方法来找到合适的种子点，帮助区域生长算法完成分割任务，达到满足要求的分割效果，分割方法流程如图8所示。

图8 分割流程图
首先对输入的图片进行灰度化处理，变成单通道的灰度图片，然后滤波去除噪声，使图像更平滑，选择合适的阈值进行阈值分割，在利用开运算去除掉分割后较小的前景，以各前景区域的中心点为起始种子点，进行区域生长，得到最终所满足要求的前景。

⛄二、部分源代码

function varargout = fruit_identify(varargin)
% FRUIT_IDENTIFY M-file for fruit_identify.fig
% FRUIT_IDENTIFY, by itself, creates a new FRUIT_IDENTIFY or raises the existing
% singleton*.
%
% H = FRUIT_IDENTIFY returns the handle to a new FRUIT_IDENTIFY or the handle to
% the existing singleton*.
%
% FRUIT_IDENTIFY(‘CALLBACK’,hObject,eventData,handles,…) calls the local
% function named CALLBACK in FRUIT_IDENTIFY.M with the given input arguments.
%
% FRUIT_IDENTIFY(‘Property’,‘Value’,…) creates a new FRUIT_IDENTIFY or raises the
% existing singleton*. Starting from the left, property value pairs are
% applied to the GUI before fruit_identify_OpeningFcn gets called. An
% unrecognized property name or invalid value makes property application
% stop. All inputs are passed to fruit_identify_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 fruit_identify

% Last Modified by GUIDE v2.5 22-May-2021 10:27:49

% Begin initialization code - DO NOT EDIT
gui_Singleton = 1;
gui_State = struct(‘gui_Name’, mfilename, …
‘gui_Singleton’, gui_Singleton, …
‘gui_OpeningFcn’, @fruit_identify_OpeningFcn, …
‘gui_OutputFcn’, @fruit_identify_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 fruit_identify is made visible.
function fruit_identify_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 fruit_identify (see VARARGIN)

% Choose default command line output for fruit_identify
handles.output = hObject;
im=imread(‘pic.jpg’);
axes(handles.axes1)
imshow(im)

% Update handles structure
guidata(hObject, handles);

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

% — Outputs from this function are returned to the command line.
function varargout = fruit_identify_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 popupmenu1.
function popupmenu1_Callback(hObject, eventdata, handles)
% hObject handle to popupmenu1 (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 popupmenu1 contents as cell array
% contents{get(hObject,‘Value’)} returns selected item from popupmenu1

% — Executes during object creation, after setting all properties.
function popupmenu1_CreateFcn(hObject, eventdata, handles)
% hObject handle to popupmenu1 (see GCBO)
% eventdata reserved - to be defined in a future version of MATLAB
% handles empty - handles not created until after all CreateFcns called

% Hint: popupmenu 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 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

function edit2_Callback(hObject, eventdata, handles)
% hObject handle to edit2 (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 edit2 as text
% str2double(get(hObject,‘String’)) returns contents of edit2 as a double

% — Executes during object creation, after setting all properties.
function edit2_CreateFcn(hObject, eventdata, handles)
% hObject handle to edit2 (see GCBO)
% eventdata reserved - to be defined in a future version of MATLAB
% handles empty - handles not created until after all CreateFcns called

function edit3_Callback(hObject, eventdata, handles)
% hObject handle to edit3 (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 edit3 as text
% str2double(get(hObject,‘String’)) returns contents of edit3 as a double

% — Executes during object creation, after setting all properties.
function edit3_CreateFcn(hObject, eventdata, handles)
% hObject handle to edit3 (see GCBO)
% eventdata reserved - to be defined in a future version of MATLAB
% handles empty - handles not created until after all CreateFcns called

function edit4_Callback(hObject, eventdata, handles)
% hObject handle to edit4 (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 edit4 as text
% str2double(get(hObject,‘String’)) returns contents of edit4 as a double

% — Executes during object creation, after setting all properties.
function edit4_CreateFcn(hObject, eventdata, handles)
% hObject handle to edit4 (see GCBO)
% eventdata reserved - to be defined in a future version of MATLAB
% handles empty - handles not created until after all CreateFcns called

function edit5_Callback(hObject, eventdata, handles)
% hObject handle to edit5 (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 edit5 as text
% str2double(get(hObject,‘String’)) returns contents of edit5 as a double

% — Executes during object creation, after setting all properties.
function edit5_CreateFcn(hObject, eventdata, handles)
% hObject handle to edit5 (see GCBO)
% eventdata reserved - to be defined in a future version of MATLAB
% handles empty - handles not created until after all CreateFcns called