【影象識別】基於BP神經網路求解車牌識別問題matlab程式碼
2022-01-02 18:00:02
1 簡介
隨著資訊時代的到來，現代智慧交通系統能夠很輕易的識別出汽車牌照，這是智慧交通管理的標誌之一。智慧交通管理系統的牌照識別集合了影象採集和預處理、車牌定位技術、字元分割和字元識別等相關技術。其中，車牌定位、字元分割和字元識別是最關鍵的技術，也是本次畢業設計的難點所在。正確利用好這三種關鍵技術，將有助於牌照識別的實時性和準確性，對於智慧交通系統的實現有著決定性作用。在MATLAB軟體開發環境下，系統首先對影象進行預處理、然後將預處理後的影象進行定位分割，最後識別出相應牌照上的字元，這樣就可以模擬設計出汽車牌照識別系統。本文的影象預處理模組是將影象灰度化和用Canny運算元進行邊緣檢測，汽車牌照定位依據是它的顏色特徵，使用MATLAB中的Radon函數和Imrotate函數來進行車牌矯正；分割字元時，需要先找到連續的文字塊，然後根據長度大小來確定是否分割，假如所找到的連續文字塊的長度大於閾值，那麼就表示可以對此文字塊進行分割。並且為了能對車牌上的字元進行正確的識別，本文將採用BP神經網路演演算法。最後設計GUI介面，使介面更加簡潔明瞭，便於操作。根據實驗得出的結論，這種方式可以對藍色的車牌進行高效、精確的識別，同時，也對光照、旋轉和噪聲表現出很好的魯棒性，定位精度和識別正確率甚至可以超過90%。
2 部分程式碼
function varargout = run(varargin)
% RUN MATLAB code for run.fig
% RUN, by itself, creates a new RUN or raises the existing
% singleton*.
%
% H = RUN returns the handle to a new RUN or the handle to
% the existing singleton*.
%
% RUN('CALLBACK',hObject,eventData,handles,...) calls the local
% function named CALLBACK in RUN.M with the given input arguments.
%
% RUN('Property','Value',...) creates a new RUN or raises the
% existing singleton*. Starting from the left, property value pairs are
% applied to the GUI before run_OpeningFcn gets called. An
% unrecognized property name or invalid value makes property application
% stop. All inputs are passed to run_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 run
% Last Modified by GUIDE v2.5 07-May-2016 15:41:22
% Begin initialization code - DO NOT EDIT
gui_Singleton = 1;
gui_State = struct('gui_Name', mfilename, ...
'gui_Singleton', gui_Singleton, ...
'gui_OpeningFcn', @run_OpeningFcn, ...
'gui_OutputFcn', @run_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 run is made visible.
function run_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 run (see VARARGIN)
% Choose default command line output for run
handles.output = hObject;
handles.cd0 = cd;
handles.Color = 0;
handles.I = [];
axes(handles.axes1);
set(gca,'Xtick',[]);
set(gca,'Ytick',[]);
box on;
axes(handles.axes2);
set(gca,'Xtick',[]);
set(gca,'Ytick',[]);
box on;
%axes(handles.axes3);
%set(gca,'Xtick',[]);
%set(gca,'Ytick',[]);
%box on;
axes(handles.axes4);
set(gca,'Xtick',[]);
set(gca,'Ytick',[]);
box on;
axes(handles.axes5);
set(gca,'Xtick',[]);
set(gca,'Ytick',[]);
box on;
axes(handles.axes6);
set(gca,'Xtick',[]);
set(gca,'Ytick',[]);
box on;
axes(handles.axes8);
set(gca,'Xtick',[]);
set(gca,'Ytick',[]);
box on;
axes(handles.axes9);
set(gca,'Xtick',[]);
set(gca,'Ytick',[]);
box on;
axes(handles.axes12);
set(gca,'Xtick',[]);
set(gca,'Ytick',[]);
box on;
axes(handles.axes13);
set(gca,'Xtick',[]);
set(gca,'Ytick',[]);
box on;
axes(handles.axes14);
set(gca,'Xtick',[]);
set(gca,'Ytick',[]);
box on;
axes(handles.axes15);
set(gca,'Xtick',[]);
set(gca,'Ytick',[]);
box on;
axes(handles.axes16);
set(gca,'Xtick',[]);
set(gca,'Ytick',[]);
box on;
axes(handles.axes17);
set(gca,'Xtick',[]);
set(gca,'Ytick',[]);
box on;
% Update handles structure
guidata(hObject, handles);
% UIWAIT makes run wait for user response (see UIRESUME)
% uiwait(handles.figure1);
% --- Outputs from this function are returned to the command line.
function varargout = run_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)
%% 讀圖
[filename, cd1] = uigetfile( ...
{'*.tif;*.TIF;*.JPG;*.jpg;*.bmp;*.BMP;*.jpeg;*.JPEG;','Image file';...
'*.*', 'All file (*.*)'},'Pick an Image');
axes(handles.axes1);
cla;
axes(handles.axes2);
cla;
%axes(handles.axes3);
%cla;
axes(handles.axes4);
cla;
if filename
cd(cd1);
d = imread(filename);
cd(handles.cd0);
handles.I = d;
axes(handles.axes1);
imshow(d);
handles.filename = filename;
box on;
end
handles.Color = 0;
cd(handles.cd0);
set(handles.text2,'string','');
guidata(hObject, handles);
% --- 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)
image = handles.I;
gray = rgb2gray(image); % 影象灰度化
axes(handles.axes2);
imshow(gray);
% --- 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)
%image = handles.I;
%gray = rgb2gray(image);
%new_gray = histeq(gray); % 直方圖均衡 ，影象增強
%axes(handles.axes3);
%imshow(new_gray);
% --- Executes on button press in pushbutton4.
function pushbutton4_Callback(hObject, eventdata, handles)
% hObject handle to pushbutton4 (see GCBO)
% eventdata reserved - to be defined in a future version of MATLAB
% handles structure with handles and user data (see GUIDATA)
image = handles.I;
gray = rgb2gray(image);
new_gray = histeq(gray); % 直方圖均衡 ，影象增強
if size(new_gray,1)>1000
new_gray_1 = imresize(new_gray,0.1);
else
new_gray_1 =new_gray;
end
bw = edge(new_gray_1,'canny');
axes(handles.axes4);
imshow(bw);
guidata(hObject, handles);
% --- Executes on button press in pushbutton9.
function pushbutton9_Callback(hObject, eventdata, handles)
% hObject handle to pushbutton9 (see GCBO)
% eventdata reserved - to be defined in a future version of MATLAB
% handles structure with handles and user data (see GUIDATA)
%% 字元識別
images_test_all = handles.testnum;
nnmain;
for i = 1:size(images_test_all,2)
images_test = double(images_test_all(:,i));
pred(i) = predict(Theta1, Theta2, images_test');
end
chepai = [];
for i = 1:size(pred,2)
if pred(i)>0
chepai = [chepai,Name{pred(i)}];
end
end
% chepai(1) = '蘇';
set(handles.text2,'string',chepai);
% --- Executes on button press in pushbutton10.
function pushbutton10_Callback(hObject, eventdata, handles)
% hObject handle to pushbutton10 (see GCBO)
% eventdata reserved - to be defined in a future version of MATLAB
% handles structure with handles and user data (see GUIDATA)
%% 這個按鈕關閉軟體
close all;
clear;
clc;
3 模擬結果
4 參考文獻
[1]馮知凡. 基於影象處理及BP神經網路的車牌識別技術的研究. Diss. 武漢科技大學, 2011.
部分理論參照網路文獻，若有侵權聯絡博主刪除。
5 MATLAB程式碼與資料下載地址
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