标签：MAIN 图像识别 gui RGB hObject handles dw main GUI
- 课题介绍
本设计为基于MATLAB的人民币识别系统。带有一个GUI界面。先利用radon进行倾斜校正，根据不同纸币，选择不同维度的参数识别纸币金额，有通过RGB分量识别100元；
通过面额图像的宽度识别1元、5元；通过构建矩形结构体识别10元 ；通过RGB分量识别 20元 与 50元。
function varargout = main(varargin)
% MAIN MATLAB code for main.fig
% MAIN, by itself, creates a new MAIN or raises the existing
% singleton*.
%
% H = MAIN returns the handle to a new MAIN or the handle to
% the existing singleton*.
%
% MAIN('CALLBACK',hObject,eventData,handles,...) calls the local
% function named CALLBACK in MAIN.M with the given input arguments.
%
% MAIN('Property','Value',...) creates a new MAIN or raises the
% existing singleton*. Starting from the left, property value pairs are
% applied to the GUI before main_OpeningFcn gets called. An
% unrecognized property name or invalid value makes property application
% stop. All inputs are passed to main_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 main
% Last Modified by GUIDE v2.5 29-May-2020 00:04:07
% Begin initialization code - DO NOT EDIT
gui_Singleton = 1;
gui_State = struct('gui_Name', mfilename, ...
'gui_Singleton', gui_Singleton, ...
'gui_OpeningFcn', @main_OpeningFcn, ...
'gui_OutputFcn', @main_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 main is made visible.
function main_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 main (see VARARGIN)
% Choose default command line output for main
handles.output = hObject;
% Update handles structure
guidata(hObject, handles);
% UIWAIT makes main wait for user response (see UIRESUME)
% uiwait(handles.figure1);
% --- Outputs from this function are returned to the command line.
function varargout = main_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)
%% 图像读取
[filename, pathname] = uigetfile({'*.jpg;*.tif;*.png;*.gif','All Image Files';...
'*.*','All Files' });
l = imread([ pathname,filename]);
axes(handles.axes1)
imshow(l);
title('原始图像')
l1=rgb2gray(l); %将真彩色图像转换为灰度图像
bw1=edge(l1,'sobel', 'both'); %采用sobel算子进行边缘检测
handles.bw1=bw1;
theta=0:179; %定义theta角度范围
r=radon(bw1,theta); %对图像进行Radon变换
%%%%%检测Radon变换矩阵中的峰值所对应的列坐标%%%%
[m,n]=size(r);
c=1;
for i=1:m
for j=1:n
if r(1,1)<r(i,j)
r(1,1)=r(i,j);
c=j;
end
end
end
rot=90-c;
pic=imrotate(l,rot,'crop'); %对图片进行旋转矫正
handles.pic=pic;
pic_gray=rgb2gray(pic); %转换为灰度图像
handles.pic_gray=pic_gray;
pic_a=imadjust(pic_gray,[0,0.001],[1,0]); %明暗反转
pic_b=1.3*pic_gray+0.7*pic_a;
pic_c=imadjust(pic_b,[0.5,1],[0,1]); %明暗反转
handles.pic_c=pic_c;
pic_b_edge=edge(pic_c,'sobel'); %采用sobel算子进行边缘检测
handles.pic_b_edge=pic_b_edge;
se=[1;1;1]; %线型结构元素
pic_imerode=imerode(pic_b_edge,se); %腐蚀图像
handles.pic_imerode=pic_imerode;
se=strel('rectangle',[60,60]); %矩形结构元素
pic_imclose=imclose(pic_imerode,se); %图像聚类、填充图像
handles.pic_imclose=pic_imclose;
pic_bwareaopen=bwareaopen(pic_imclose,10000); %去除聚团灰度值小于10000的部分
%%%%%求纸币行起始位置和终止位置%%%%%
[y,x]=size(pic_bwareaopen);
I6=double(pic_bwareaopen);
Y1=zeros(y,1);
for i=1:y
for j=1:x
if(I6(i,j,1)==1)
Y1(i,1)= Y1(i,1)+1;
end
end
end
[temp MaxY]=max(Y1);
%%
%%%%%%求纸币列起始位置和终止位置%%%%%
PY1=MaxY;
while ((Y1(PY1,1)>=50)&&(PY1>1))
PY1=PY1-1;
end
PY2=MaxY;
while ((Y1(PY2,1)>=50)&&(PY2<y))
PY2=PY2+1;
end
IY=pic(PY1:PY2,:,:);
X1=zeros(1,x);
for j=1:x
for i=PY1:PY2
if(I6(i,j,1)==1)
X1(1,j)= X1(1,j)+1;
end
end
end
%%
%%提取并画出背景中的RMB图像%%
PX1=1;
while ((X1(1,PX1)<3)&&(PX1<x))
PX1=PX1+1;
end
PX2=x;
while ((X1(1,PX2)<3)&&(PX2>PX1))
PX2=PX2-1;
end
dw=pic(PY1:PY2,PX1:PX2,:);
dw_gray=rgb2gray(dw);
dw_gray=imadjust(dw_gray,[0,1],[1,0]);
dw_bw=im2bw(dw_gray);
handles.dw_bw=dw_bw;
%%
%%分割提取RMB数值图像%%
[m,n]=size(dw_bw);
m1=round(m/3);
m2=round(2*m/3);
n1=round(n/6);
n2=round(n/3);
n3=round(2*n/3);
n4=round(5*n/6);
sum1=sum(sum(dw_bw(m1:m2,n1:n2)));
sum2=sum(sum(dw_bw(m1:m2,n3:n4)));
if sum1>sum2
dw=imrotate(dw,180,'crop');
end
%%
%%图像处理%%
x=dw;
x1=imresize(x,[236,500]);%'缩放图像
z=imcrop(x1,[270,150,160,65]);%对图像进行剪切，选取有效区域
%%
I=imcrop(x1,[130,60,130,65]); %对图像进行剪切，选取有效区域
handles.I=I;
I1=rgb2gray(I); %转换为灰度图像
I2=medfilt2(I1); %滤波默认窗口
I3=imadjust(I2,[0.3,0.5],[0,1],1); %明暗反转
I4=im2bw(I3);
handles.I4=I4;
se=strel('rectangle',[3,3]); %构造结构函数，以长方形构造一个se
标签：MAIN,图像识别,gui,RGB,hObject,handles,dw,main,GUI 来源： https://blog.51cto.com/u_15287693/2978811
本站声明： 1. iCode9 技术分享网（下文简称本站）提供的所有内容，仅供技术学习、探讨和分享； 2. 关于本站的所有留言、评论、转载及引用，纯属内容发起人的个人观点，与本站观点和立场无关； 3. 关于本站的所有言论和文字，纯属内容发起人的个人观点，与本站观点和立场无关； 4. 本站文章均是网友提供，不完全保证技术分享内容的完整性、准确性、时效性、风险性和版权归属；如您发现该文章侵犯了您的权益，可联系我们第一时间进行删除； 5. 本站为非盈利性的个人网站，所有内容不会用来进行牟利，也不会利用任何形式的广告来间接获益，纯粹是为了广大技术爱好者提供技术内容和技术思想的分享性交流网站。