MATLAB GUIDELINES FOR BEGINEER

SIMULINK MODEL FOR THREE PHASE FAULT DETECTION

SOURCE CODE FOR VEHICLE NUMBER PLATE DETECTION USING MATLAB IMAGE PROCESSING

clc; % Clear command window.
clear all; % Delete all variables.
close all; % Close all figure windows except those created by imtool.
imtool close all; % Close all figure windows created by imtool.
workspace; % Make sure the workspace panel is showing.
% Read Image
I = imread ('CAR3.jpg');
figure(1);
imshow(I);
% Extract Y component (Convert an Image to Gray)
Igray = rgb2gray(I);
[rows cols] = size(Igray);
%% Dilate and Erode Image in order to remove noise
Idilate = Igray;
for i = 1:rows
for j = 2:cols-1
temp = max(Igray(i,j-1), Igray(i,j));
Idilate(i,j) = max(temp, Igray(i,j+1));
end
end
I = Idilate;
figure(2);
imshow(Igray);
figure(3);
title('Dilated Image')
imshow(Idilate);
figure(4);
imshow(I);
difference = 0;
sum = 0;
total_sum = 0;
difference = uint32(difference);
%% PROCESS EDGES IN HORIZONTAL DIRECTION
disp('Processing Edges Horizontally...');
max_horz = 0;
maximum = 0;
for i = 2:cols
sum = 0;
for j = 2:rows
if(I(j, i) > I(j-1, i))
difference = uint32(I(j, i) - I(j-1, i));
else
difference = uint32(I(j-1, i) - I(j, i));
end
if(difference > 20)
sum = sum + difference;
end
end
horz1(i) = sum;
% Find Peak Value
if(sum > maximum)
max_horz = i;
maximum = sum;
end
total_sum = total_sum + sum;
end
average = total_sum / cols;
figure(5);
% Plot the Histogram for analysis
subplot(3,1,1);
plot (horz1);
title('Horizontal Edge Processing Histogram');
xlabel('Column Number ->');
ylabel('Difference ->');
%% Smoothen the Horizontal Histogram by applying Low Pass Filter
sum = 0;
horz = horz1;
for i = 21:(cols-21)
sum = 0;
for j = (i-20):(i+20)
sum = sum + horz1(j);
end
horz(i) = sum / 41;
end
subplot(3,1,2);
plot (horz);
title('Histogram after passing through Low Pass Filter');
xlabel('Column Number ->');
ylabel('Difference ->');
%% Filter out Horizontal Histogram Values by applying Dynamic Threshold
disp('Filter out Horizontal Histogram...');
for i = 1:cols
if(horz(i) < average)
horz(i) = 0;
for j = 1:rows
I(j, i) = 0;
end
end
end
subplot(3,1,3);
plot (horz);
title('Histogram after Filtering');
xlabel('Column Number ->');
ylabel('Difference ->');
%% PROCESS EDGES IN VERTICAL DIRECTION
difference = 0;
total_sum = 0;
difference = uint32(difference);
disp('Processing Edges Vertically...');
maximum = 0;
max_vert = 0;
for i = 2:rows
sum = 0;
for j = 2:cols %cols
if(I(i, j) > I(i, j-1))
difference = uint32(I(i, j) - I(i, j-1));
end
if(I(i, j) <= I(i, j-1))
difference = uint32(I(i, j-1) - I(i, j));
end
if(difference > 20)
sum = sum + difference;
end
end
vert1(i) = sum;
%% Find Peak in Vertical Histogram
if(sum > maximum)
max_vert = i;
maximum = sum;
end
total_sum = total_sum + sum;
end
average = total_sum / rows;
figure(6)
subplot(3,1,1);
plot (vert1);
title('Vertical Edge Processing Histogram');
xlabel('Row Number ->');
ylabel('Difference ->');
%% Smoothen the Vertical Histogram by applying Low Pass Filter
disp('Passing Vertical Histogram through Low Pass Filter...');
sum = 0;
vert = vert1;
for i = 21:(rows-21)
sum = 0;
for j = (i-20):(i+20)
sum = sum + vert1(j);
end
vert(i) = sum / 41;
end
subplot(3,1,2);
plot (vert);
title('Histogram after passing through Low Pass Filter');
xlabel('Row Number ->');
ylabel('Difference ->');
%% Filter out Vertical Histogram Values by applying Dynamic Threshold
disp('Filter out Vertical Histogram...');
for i = 1:rows
if(vert(i) < average)
vert(i) = 0;
for j = 1:cols
I(i, j) = 0;
end
end
end
subplot(3,1,3);
plot (vert);
title('Histogram after Filtering');
xlabel('Row Number ->');
ylabel('Difference ->');
figure(7), imshow(I);
%% Find Probable candidates for Number Plate
j = 1;
for i = 2:cols-2
if(horz(i) ~= 0 && horz(i-1) == 0 && horz(i+1) == 0)
column(j) = i;
column(j+1) = i;
j = j + 2;
elseif((horz(i) ~= 0 && horz(i-1) == 0) || (horz(i) ~= 0 && horz(i+1) == 0))
column(j) = i;
j = j+1;
end
end
j = 1;
for i = 2:rows-2
if(vert(i) ~= 0 && vert(i-1) == 0 && vert(i+1) == 0)
row(j) = i;
row(j+1) = i;
j = j + 2;
elseif((vert(i) ~= 0 && vert(i-1) == 0) || (vert(i) ~= 0 && vert(i+1) == 0))
row(j) = i;
j = j+1;
end
end
[temp column_size] = size (column);
if(mod(column_size, 2))
column(column_size+1) = cols;
end
[temp row_size] = size (row);
if(mod(row_size, 2))
row(row_size+1) = rows;
end
%% Region of Interest Extraction
%Check each probable candidate
for i = 1:2:row_size
for j = 1:2:column_size
% If it is not the most probable region remove it from image
if(~((max_horz >= column(j) && max_horz <= column(j+1)) && (max_vert >=row(i) && max_vert <= row(i+1))))
%This loop is only for displaying proper output to User
for m = row(i):row(i+1)
for n = column(j):column(j+1)
I(m, n) = 0;
end
end
end
end
end
figure(8), imshow(I);
imshow(I);

SOURCE CODE FOR GESTURE RECOGNITION USING MATLAB IMAGE PROCESSING

function gesturerecognisition(redThresh, greenThresh, blueThresh, numFrame)
warning('off','vision:transition:usesOldCoordinates');

if nargin < 1
    redThresh = 0.22;
    greenThresh = 0.14;
    blueThresh = 0.18;
    numFrame = 1000;
end

cam = imaqhwinfo;
cameraName = char(cam.InstalledAdaptors(end));
cameraInfo = imaqhwinfo(cameraName);
cameraId = cameraInfo.DeviceInfo.DeviceID(end);
cameraFormat = char(cameraInfo.DeviceInfo.SupportedFormats(end));

jRobot = java.awt.Robot;
vidDevice = imaq.VideoDevice(cameraName, cameraId, cameraFormat, ...
                    'ReturnedColorSpace', 'RGB');

vidInfo = imaqhwinfo(vidDevice);
screenSize = get(0,'ScreenSize');
hblob = vision.BlobAnalysis('AreaOutputPort', false, ...
                                'CentroidOutputPort', true, ...
                                'BoundingBoxOutputPort', true', ...
                                'MaximumBlobArea', 3000, ...
                                'MinimumBlobArea', 100, ...
                                'MaximumCount', 3);
hshapeinsBox = vision.ShapeInserter('BorderColorSource', 'Input port', ...
                                    'Fill', true, ...
                                    'FillColorSource', 'Input port', ...
                                    'Opacity', 0.4);
hVideoIn = vision.VideoPlayer('Name', 'Final Video', ...
                                'Position', [100 100 vidInfo.MaxWidth+20 vidInfo.MaxHeight+30]);
nFrame = 0;
lCount = 0; rCount = 0; dCount = 0;
sureEvent = 5;
iPos = vidInfo.MaxWidth/2;


while (nFrame < numFrame)
    rgbFrame = step(vidDevice);
    rgbFrame = flipdim(rgbFrame,2);
    diffFrameRed = imsubtract(rgbFrame(:,:,1), rgb2gray(rgbFrame));
    binFrameRed = im2bw(diffFrameRed, redThresh);
    [centroidRed, bboxRed] = step(hblob, binFrameRed);

    diffFrameGreen = imsubtract(rgbFrame(:,:,2), rgb2gray(rgbFrame));
    binFrameGreen = im2bw(diffFrameGreen, greenThresh);
    [centroidGreen, bboxGreen] = step(hblob, binFrameGreen);
 
    diffFrameBlue = imsubtract(rgbFrame(:,:,3), rgb2gray(rgbFrame));
    binFrameBlue = im2bw(diffFrameBlue, blueThresh);
    [~, bboxBlue] = step(hblob, binFrameBlue);
 
    if length(bboxRed(:,1)) == 1
        jRobot.mouseMove(1.5*centroidRed(:,1)*screenSize(3)/vidInfo.MaxWidth, 1.5*centroidRed(:,2)*screenSize(4)/vidInfo.MaxHeight);
    end
    if ~isempty(bboxBlue(:,1))
        if length(bboxBlue(:,1)) == 1
            lCount = lCount + 1;
            if lCount == sureEvent
                jRobot.mousePress(16);
                pause(0.1);
                jRobot.mouseRelease(16);
            end
        elseif length(bboxBlue(:,1)) == 2
            rCount = rCount + 1;
            if rCount == sureEvent
                jRobot.mousePress(4);
                pause(0.1);
                jRobot.mouseRelease(4);
            end
        elseif length(bboxBlue(:,1)) == 3
            dCount = dCount + 1;
            if dCount == sureEvent
                jRobot.mousePress(16);
                pause(0.1);
                jRobot.mouseRelease(16);
                pause(0.2);
                jRobot.mousePress(16);
                pause(0.1);
                jRobot.mouseRelease(16);
            end
        end
    else
        lCount = 0; rCount = 0; dCount = 0;
    end
    if ~isempty(bboxGreen(:,1))
        if (mean(centroidGreen(:,2)) - iPos) < -2
            jRobot.mouseWheel(-1);
        elseif (mean(centroidGreen(:,2)) - iPos) > 2
            jRobot.mouseWheel(1);
        end
        iPos = mean(centroidGreen(:,2));
    end
    vidIn = step(hshapeinsBox, rgbFrame, bboxRed,single([1 0 0]));
    vidIn = step(hshapeinsBox, vidIn, bboxGreen,single([0 1 0]));
    vidIn = step(hshapeinsBox, vidIn, bboxBlue,single([0 0 1]));
    step(hVideoIn, vidIn);
    nFrame = nFrame+1;
end

release(hVideoIn);
release(vidDevice);
clc;
end

SOURCE CODE FOR REAL TIME FACE DETECTION USING IMAGE PROCESSING MATLAB

function varargout = testing(varargin)
% TESTING MATLAB code for testing.fig
%      TESTING, by itself, creates a new TESTING or raises the existing
%      singleton*.
%
%      H = TESTING returns the handle to a new TESTING or the handle to
%      the existing singleton*.
%
%      TESTING('CALLBACK',hObject,eventData,handles,...) calls the local
%      function named CALLBACK in TESTING.M with the given input arguments.
%
%      TESTING('Property','Value',...) creates a new TESTING or raises the
%      existing singleton*.  Starting from the left, property value pairs are
%      applied to the GUI before testing_OpeningFcn gets called.  An
%      unrecognized property name or invalid value makes property application
%      stop.  All inputs are passed to testing_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 testing

% Last Modified by GUIDE v2.5 20-Aug-2013 16:34:04

% Begin initialization code - DO NOT EDIT
gui_Singleton = 1;
gui_State = struct('gui_Name',       mfilename, ...
                   'gui_Singleton',  gui_Singleton, ...
                   'gui_OpeningFcn', @testing_OpeningFcn, ...
                   'gui_OutputFcn',  @testing_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 testing is made visible.
function testing_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 testing (see VARARGIN)

% Choose default command line output for testing
handles.output = hObject;
axes(handles.axes1);
imshow('blank.jpg');
axis off;
% Update handles structure
guidata(hObject, handles);

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


% --- Outputs from this function are returned to the command line.
function varargout = testing_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 start.
function start_Callback(hObject, eventdata, handles)
% hObject    handle to start (see GCBO)
% eventdata  reserved - to be defined in a future version of MATLAB
% handles    structure with handles and user data (see GUIDATA)
handles.vid = videoinput('winvideo' , 1, 'YUY2_640X480');
%preview(handles.vid);
guidata(hObject, handles);

% --- Executes on button press in face.
function face_Callback(hObject, eventdata, handles)
% hObject    handle to face (see GCBO)
% eventdata  reserved - to be defined in a future version of MATLAB
% handles    structure with handles and user data (see GUIDATA)
%handles.vid = videoinput('winvideo' , 1, 'YUY2_640X480');
triggerconfig(handles.vid ,'manual');
set(handles.vid, 'TriggerRepeat',inf);
set(handles.vid, 'FramesPerTrigger',1);
handles.vid.ReturnedColorspace = 'rgb';
 handles.vid.Timeout = 5;
start(handles.vid);
while(1)

facedetector = vision.CascadeObjectDetector;                                              
trigger(handles.vid);
handles.im = getdata(handles.vid, 1);
bbox = step(facedetector, handles.im);
hello = insertObjectAnnotation(handles.im,'rectangle',bbox,'Face');
imshow(hello);
end
guidata(hObject, handles);


% --- Executes on button press in stop.
function stop_Callback(hObject, eventdata, handles)
% hObject    handle to stop (see GCBO)
% eventdata  reserved - to be defined in a future version of MATLAB
% handles    structure with handles and user data (see GUIDATA)
handles.output = hObject;
stop(handles.vid),clear handles.vid %, ,delete(handles.vid)
guidata(hObject, handles);


% --- Executes on button press in eyes.
function eyes_Callback(hObject, eventdata, handles)
% hObject    handle to eyes (see GCBO)
% eventdata  reserved - to be defined in a future version of MATLAB
% handles    structure with handles and user data (see GUIDATA)
triggerconfig(handles.vid ,'manual');
set(handles.vid, 'TriggerRepeat',inf);
set(handles.vid, 'FramesPerTrigger',1);
handles.vid.ReturnedColorspace = 'rgb';
 handles.vid.Timeout = 2;
start(handles.vid);
while(1)
bodyDetector = vision.CascadeObjectDetector('EyePairBig');
bodyDetector.MinSize = [11 45];
%bodyDetector.ScaleFactor = 1.05;                                              
trigger(handles.vid);
handles.im = getdata(handles.vid, 1);
bbox = step(bodyDetector, handles.im);
hello = insertObjectAnnotation(handles.im,'rectangle',bbox,'EYE');
imshow(hello);
end
guidata(hObject, handles);


% --- Executes on button press in upperbody.
function upperbody_Callback(hObject, eventdata, handles)
% hObject    handle to upperbody (see GCBO)
% eventdata  reserved - to be defined in a future version of MATLAB
% handles    structure with handles and user data (see GUIDATA)
triggerconfig(handles.vid ,'manual');
set(handles.vid, 'TriggerRepeat',inf);
set(handles.vid, 'FramesPerTrigger',1);
handles.vid.ReturnedColorspace = 'rgb';
 handles.vid.Timeout = 5;
start(handles.vid);
while(1)
bodyDetector = vision.CascadeObjectDetector('UpperBody');
bodyDetector.MinSize = [60 60];
bodyDetector.ScaleFactor = 1.05;                                              
trigger(handles.vid);
handles.im = getdata(handles.vid, 1);
bbox = step(bodyDetector, handles.im);
hello = insertObjectAnnotation(handles.im,'rectangle',bbox,'UpperBody');
imshow(hello);
end
guidata(hObject, handles);