% this is include on GUI MATLAB so u can learn faster
function fourier_transform
global edit1 edit2 ax1 ax2 check1 text3
f = figure('Name','Fourier Transformation','MenuBar','none',...
    'ToolBar','none','NumberTitle','off','Position',[250 130 800 500]);

ax1 = axes('Position',[.3 .55 .65 .3],'XTick',[],...
    'YTick',[],'Visible','on');

ax2 = axes('Position',[.3 .1 .65 .3],'XTick',[],...
    'YTick',[],'Visible','on');

panel1 = uipanel('Title','Panel','FontWeight','bold',...
    'FontSize',10,'Position',[.05 .5 .2 .37]);

edit1 = uicontrol('Parent',panel1,'Style','edit','Position',[95 120 50 30]);
edit2 = uicontrol('Parent',panel1,'Style','edit','Position',[95 80 50 30]);

push1 = uicontrol('Parent',panel1,'Style','pushbutton',...
    'Position',[10 15 130 30],'String','Plot','FontSize',10,...
    'Callback',@pushbutton1);

check1 = uicontrol('Parent',panel1,'Style','checkbox',...
    'Position',[10 45 130 30],'String','Random Noise','FontSize',10,...
    'Callback',@checkbutton1);

text1 = uicontrol('Parent',panel1,'Style','text',...
    'Position',[10 115 80 30],'String','Frequency 1','FontSize',10);

text2 = uicontrol('Parent',panel1,'Style','text',...
    'Position',[10 75 80 30],'String','Frequency 2','FontSize',10);
% formula
text3 = uicontrol('Style','text','Position',[350 450 300 30],...
    'String','y = sin(2*pi*f1*t) + sin(2*pi*f2*t)','FontSize',10);
% random noise when this check button on + 2*randn(size(t))
function checkbutton1(~,~)
global check1 text3
val = get(check1,'Value');
switch val
    case 0
        set(text3,'String','y = sin(2*pi*f1*t) + sin(2*pi*f2*t)');
    case 1
        set(text3,'String','y = sin(2*pi*f1*t) + sin(2*pi*f2*t) + 2*randn(size(t))');
end
% execute program 
function pushbutton1(~,~)
global edit1 edit2 ax1 ax2 check1

val = get(check1,'Value');
switch val
    case 0
        t = 0:.001:.25;
        f1 = str2double(get(edit1,'String'));
        f2 = str2double(get(edit2,'String'));
        
        % Calculate data
        x = sin(2*pi*f1*t) + sin(2*pi*f2*t);
        % fft is fourier transform and we can change to time domain
        y = fft(x,512);
        m = y.*conj(y)/512;
        f = 1000*(0:256)/512;
        
        % Create time plot 
        axes(ax1) % Select the proper axes
        plot(t,x)
        set(ax1,'XMinorTick','on')
        grid on
        title('Time Domain') % plot time domain
        
        % Create frequency plot
        axes(ax2) % Select the proper axes
        plot(f,m(1:257))
        set(ax2,'XMinorTick','on')
        grid on
        title('Frequency Domain') % plot freq domain
    case 1
        t = 0:.001:.25; %scale of plot
        f1 = str2double(get(edit1,'String'));
        f2 = str2double(get(edit2,'String'));
        
        % Calculate data
        x = sin(2*pi*f1*t) + sin(2*pi*f2*t) + 2*randn(size(t));
        y = fft(x,512);
        m = y.*conj(y)/512;
        f = 1000*(0:256)/512;
        
        % Create time plot
        axes(ax1) % Select the proper axes
        plot(t,x)
        set(ax1,'XMinorTick','on')
        grid on
        title('Time Domain')
        
        % Create frequency plot
        axes(ax2) % Select the proper axes
        plot(f,m(1:257))
        set(ax2,'XMinorTick','on')
        grid on
        title('Frequency Domain')
end

clc; clear; close all; warning off all;

%read the image
I = imread('satomi.jpg');
figure; imshow(I); %gambar 1

out = uint8(zeros(size(I,1), size(I,2), size(I,3)));

%R,G,B components of the input image
R = I(:,:,1);
G = I(:,:,2);
B = I(:,:,3);

%Inverse of the Avg values of the R,G,B
mR = 1/(mean(mean(R)));
mG = 1/(mean(mean(G)));
mB = 1/(mean(mean(B)));

%Smallest Avg Value (MAX because we are dealing with the inverses)
maxRGB = max(max(mR, mG), mB);

%Calculate the scaling factors
mR = mR/maxRGB;
mG = mG/maxRGB;
mB = mB/maxRGB;

%Scale the values
out(:,:,1) = R*mR;
out(:,:,2) = G*mG;
out(:,:,3) = B*mB;

%Convert the image from RGB to YCbCr
img_ycbcr = rgb2ycbcr(out);
figure, imshow(img_ycbcr); %gambar 2

Y = img_ycbcr(:,:,1);
Cb = img_ycbcr(:,:,2);
Cr = img_ycbcr(:,:,3);

figure, imshow(Y); %gambar 3
figure, imshow(Cb); %gambar 4
figure, imshow(Cr); %gambar 5

%Detect Skin
[r,c,v] = find(Cb>=77 & Cb<=128 & Cr>=133 & Cr<=193);
numind = size(r,1);

bin = false(size(I,1), size(I,2));

%Mark Skin Pixels
for i=1:numind
    bin(r(i),c(i)) = 1;
end

figure, imshow(bin); %gambar 6
% filling holes untuk mengisi objek yang berlubang
bin = imfill(bin,'holes');
figure, imshow(bin); %gambar 7

bin = bwareaopen(bin,500);
figure; imshow(bin); %gambar 8

R(~bin) = 0;
G(~bin) = 0;
B(~bin) = 0;
out = cat(3,R,G,B);
figure; imshow(out); %gambar 9

s = regionprops(bin,'BoundingBox');
bbox = cat(1, s.BoundingBox);

RGB = insertShape(I, 'rectangle', bbox, 'LineWidth', 5);
figure, imshow(RGB); %gambar 10

%Detect Skin
[r,c,v] = find(Cb>=77 & Cb<=128 & Cr>=133 & Cr<=193);
numind = size(r,1);

nilai batas threshold bisa dirubah sesuai nilai data pixel yang kamu batasi 

bisa dipantau pada workspace pada program Matlab untuk berasan tiap gambar yang diproses