Tutorial Machine Vision 2

Sudah cukup lama liburan dan tidak membuat entri, akhirnya ada waktu juga untuk membuat entri. Selanjutnya pada tutorial machine vision 2 ini saya akan memberi tahu bagaimana mengolah image dan menampilkan hasilnya yang telah diolah. Pada kesempatan ini juga, saya akan memberi bagaimana mengolah image tanpa API matlab, walaupun ada yang menggunakan API matlab seperti pada proses Fast Fourier Transform.

Tutorial 3 Membuat Histogram dan Menampilkan Image
 

a=imread('jeby.jpg');

subplot(2,2,1),imshow(a),title('RGB');

b=RGB2Gray(a);

i=histeq(b);

subplot(2,2,2), imshow(i),title('Histogram Equalizer');

subplot(2,2,3), imhist(i),title('Histogram');

background = imopen(i,strel('disk',5));

subplot(2,2,4), imshow(background),title('strel');

Tutorial 4 Mengolah Data Histogram

a=imread('jeby.jpg')

b=rgb2gray(a);

subplot(4,3,1), imhist(b),title('a')

subplot(4,3,2), imhist(b,5),title('b')

subplot(4,3,3), imhist(b,1),title('c')

subplot(4,3,4), imhist(b,10),title('d')

axis([0 255 0 15000])

set(gca,'xtick',0:50:255)

set(gca,'ytick',0:2000:15000)

subplot(4,3,5), imhist(b),title('e')

p=imhist(b)/numel(b);

h1=b(1:10:256);

horz=1:10:256;

bar(horz,h1)

axis([0 255 0 15000])

set(gca,'xtick',0:50:255)

set(gca,'ytick',0:2000:15000)

g=histeq(b);

subplot(4,3,6),imshow(b),title('f')

subplot(4,3,7),imhist(b),title('g')

ylim('auto')

g=histeq(b,256)

subplot(4,3,8),imshow(g),title('h')

subplot(4,3,9),imshow(a),title('i')

subplot(4,3,10),imhist(g),title('j'), subplot(4,3,11), imhist(b),title('k')

ylim('auto')

Tutorial 5 Membuat Fast Fourier Transform

a=imread('jeboy.jpg');

B=0.2989*a(:,:,1)+0.587*a(:,:,2)+0.114*a(:,:,3);subplot(2,2,1),imshow(B)

b=fft2(B);

B=fftshift(b);

subplot(2,2,2),imshow(log(abs(B)),[])

[x y]=size(B);

H=zeros(x,y);

H(.5*x-10:.5*x+10,.5*y-10:.5*y+10)=1;

subplot(2,2,3),imshow(H,[])

D=B.*H;

D=fftshift(D);

E=real(ifft2(D));

subplot(2,2,4),imshow(E,[])

Tutorial 6 Membuat Image Yang Telah di Olah

Pada tutorila ke-6 ini saya akan menggunakan Binary, Erosion, Dilation, Edge, Salt and Pepper

%%Algorithma

clear, close all

%%memanggil gambar

Z=imread('robofish.jpg');

subplot(3,4,1), imshow(Z),title('Gambar asli'),pixval on;

tic

%%mengubah RGB menjadi Grayscale

G=0.2989*Z(:,:,1)+0.587*Z(:,:,2)+0.114*Z(:,:,3);

subplot(3,4,2),imshow(G), title('Gambar Grayscale'),pixval on;

%%mencari threshold

f=imhist(G);

h=[0:255];

thres=(h*f)/(sum(f));

H=G;

[k l]=size(H);

for i=1:1:k

    for j=1:1:l

        if H(i,j)>thres

            H(i,j)=255;

        else

            H(i,j)=0;

        end

    end

end

subplot(3,4,3),imshow(H), title('Grayscale Threshold'),pixval on;

%%mengubah grayscale menjadi binary

B=im2bw(G);

subplot(3,4,4),imshow(B), title('Gambar Binary'),pixval on;

%%menggunakan errosion

[m n]=size(B);

Bb=B;

d=m-3+1;

e=n-3+1;

for i=1:1:d

    for j=1:1:e

        if (sum(sum(B(i:3+(i-1),j:3+(j-1))))-sum(B(i+1,j+1)))<8

            Bb(i+1,j+1)=0;

        else

            Bb(i+1,j+1)=B(i+1,j+1);

        end

        j=0;

    end

end

subplot(3,4,5),imshow(Bb),title('Gambar Errosion'),pixval on

%%menggunakan dilation

Dd=B;

for i=1:1:d

    for j=1:1:e

        if (sum(sum(B(i:3+(i-1),j:3+(j-1))))-sum(B(i+1,j+1)))>0

            Dd(i+1,j+1)=1;

        else

            Dd(i+1,j+1)=B(i+1,j+1);

        end

        j=0;

    end

end

subplot(3,4,6),imshow(Dd),title('Gambar Dilation'),pixval on

%%menggunakan edge

Ee=B;

for i=1:1:d

    for j=1:1:e

        if (sum(sum(B(i:3+(i-1),j:3+(j-1))))-sum(B(i+1,j+1)))==8

            Ee(i+1,j+1)=0;

        else

            Ee(i+1,j+1)=B(i+1,j+1);

        end

        j=0;

    end

end

subplot(3,4,7),imshow(Ee),title('Gambar Edge'),pixval on

%%menggunakan salt

Ff=B;

for i=1:1:d

    for j=1:1:e

        if (sum(sum(B(i:3+(i-1),j:3+(j-1))))-sum(B(i+1,j+1)))==8

            Ff(i+1,j+1)=1;

        else

            Ff(i+1,j+1)=B(i+1,j+1);

        end

        j=0;

    end

end

subplot(3,4,8),imshow(Ff),title('Gambar Salt'),pixval on

%%menggunakan Pepper

Gg=B;

for i=1:1:d

    for j=1:1:e

        if (sum(sum(B(i:3+(i-1),j:3+(j-1))))-sum(B(i+1,j+1)))==0

            Gg(i+1,j+1)=0;

        else

            Gg(i+1,j+1)=B(i+1,j+1);

        end

        j=0;

    end

end

subplot(3,4,9),imshow(Gg),title('Gambar Pepper'),pixval on

%%menggunakan Salt-Pepper

Hh=B;

for i=1:1:d

    for j=1:1:e

        if (sum(sum(B(i:3+(i-1),j:3+(j-1))))-sum(B(i+1,j+1)))==0

            Hh(i+1,j+1)=0;

        elseif (sum(sum(B(i:3+(i-1),j:3+(j-1))))-sum(B(i+1,j+1)))==8

            Hh(i+1,j+1)=1;

        else

            Hh(i+1,j+1)=B(i+1,j+1);

        end

        j=0;

    end

end

subplot(3,4,10),imshow(Hh),title('Gambar Salt-Pepper'),pixval on

%%menggunakan Edge yang telah di salt-pepper

Ii=Hh;

for i=1:1:d

    for j=1:1:e

        if (sum(sum(Hh(i:3+(i-1),j:3+(j-1))))-sum(Hh(i+1,j+1)))==8

            Ii(i+1,j+1)=0;

        else

            Ii(i+1,j+1)=Hh(i+1,j+1);

        end

        j=0;

    end

end

subplot(3,4,11),imshow(Ii),title('Gambar Edge yang telah di salt-pepper'),pixval on

toc

Tutorial 7 Menggunakan Median Filter

%%Function dari median filter

function median(I)

%I=imread('*:\Y.bmp');

figure, imshow(I),title('Gambar RGB');

I=0.2989*I(:,:,1)+0.587*I(:,:,2)+0.114*I(:,:,3);

figure, imshow(I),title('Gambar Grayscale');

[M,N]=size(I);

l=9;

w=(3-1)/2; %faktor mask 3 x 3

h=(3-1)/2; %faktor mask 3 x 3

for x=1:M

    for y=1:N

        if y<=w||y>=N-w||x<=h||x>=M-h

            K(x,y)=I(x,y);

        else

            for m=x-h:x+h

                for n=y-w:y+w

                    T(m-x+h+1,n-y+w+1)=I(m,n);

                end

            end

            temp=T(:);

            for m=1:l

                for n=1:l-m

                    if temp(n)>temp(n+1)

                        t=temp(n);

                        temp(n)=temp(n+1);

                        temp(n+1)=t;

                    end

                end

            end

            K(x,y)=temp((l+1)/2);

        end

    end

end

figure,imshow(K),title('Gambar Median Filter'), pixval on

 

 

 

Tutorial 8 Menggunakan Gaussian Filter

%%Convolution

clc, clear all, close all

rgb=imread('jeboy.jpg');

figure, imshow(rgb),title('Gambar RGB');

gr=0.2989*rgb(:,:,1)+0.587*rgb(:,:,2)+0.114*rgb(:,:,3);

figure, imshow(gr),title('Gambar Grayscale');

%matrik a diagonal edge detection mask

ed=[1 2 1;

    2 4 2;

    1 2 1];

ed=(1/16)*ed;

[k l]=size(gr);

[m n]=size(ed);

d=k-m+1;

e=l-n+1;

z1=zeros(d, e);

for i=1:d

    for j=1:e

        sum=0;

        for x=1:m

            for y=1:n

                sum=sum+gr(i-x+m,j-y+n)*ed(x,y);

            end

        end

        z1(i,j)=sum;

    end

end

figure, imshow(z1, []),title('Gambar Gaussian Convolusion');

Tutorila 9 Menggunakan Rotasi

%%Program Rotasi

clc,clear all

%%rotate

im1 = imread('jeboy.jpg');imshow(im1); 

[m,n,p]=size(im1);

thet = pi/4;

for t=1:m

   for s=1:n

      i = uint16((t-m/2)*cos(thet)-(s-n/2)*sin(thet)+m/2);

      j = uint16((t-m/2)*sin(thet)+(s-n/2)*cos(thet)+n/2);

      if i>0 && j>0 && i<=m && j<=n          

         im2(t,s,:)=im1(i,j,:);

      end

   end

end

figure,imshow(im2);

 

 Tutoral 10 Menggunakan Laplacian Filter

%%Program laplacian

f=imread('harimau.jpg');

f=im2double(f);

r=f(:,:,1);

g=f(:,:,2);

b=f(:,:,3);

[m n]=size(r);

for i=1:m

    for j=1:n

        ip=i+1;

        im=i-1;

        jm=j-1;

        jp=j+1;

        if(im<1)

            im=i;

        elseif (ip>m)

            ip=i;

        end

        if(jm<1)

            jm=j;

        elseif (jp>n)

            jp=j;

        end

        rt(i,j)=-4*r(i,j)+ 1*(r(i,jm)+r(i,jp)+r(ip,j)+r(im,j));

        gt(i,j)=-4*g(i,j)+ 1*(g(i,jm)+g(i,jp)+g(ip,j)+g(im,j));

        bt(i,j)=-4*b(i,j)+ 1*(b(i,jm)+b(i,jp)+b(ip,j)+b(im,j));

       end

end

rt=r-rt;

gt=g-gt;

bt=b-bt;

T=cat(3,rt,gt,bt);

subplot(1,2,1), imshow(f),title('Original Image');

subplot(1,2,2), imshow(T),title('Sharpened Image');

Tutorial 11 Menggunakan Intenshity Shift

%%program

clear all,clc

im=imread('harimau.jpg');

gr=0.2989.*im(:,:,1)+0.578.*im(:,:,2)+0.114.*im(:,:,3);

subplot(1,2,1),imshow(gr),title('Grayscale');

[m n]=size(gr);

k=10;

W=100;

jd=gr;

for i=1:1:m

    for j=1:1:n

        if gr(i,j)+k<0

            jd(i,j)=0;

        elseif gr(i,j)+k>=0 && gr(i,j)<=W

            jd(i,j)=im(i,j)+k;

        elseif gr(i,j)+k>W

            jd(i,j)=W;

        end

    end

end

subplot(1,2,2),imshow(jd),title('Intensity Shift');

Tutorial 12 Menggunakan Intenshity Multiple

%%program

clear all,clc

im=imread('harimau.jpg');

gr=0.2989.*im(:,:,1)+0.578.*im(:,:,2)+0.114.*im(:,:,3);

subplot(1,2,1),imshow(gr),title('Grayscale');

[m n]=size(gr);

k=10;

W=100;

jd=gr;

for i=1:1:m

    for j=1:1:n

        if gr(i,j)*k<0

            jd(i,j)=0;

        elseif gr(i,j)*k>=0 && gr(i,j)<=W

            jd(i,j)=im(i,j)*k;

        elseif gr(i,j)*k>W

            jd(i,j)=W;

        end

    end

end

subplot(1,2,2),imshow(jd),title('Intensity Shift');

 

Tutorial 13 Menggunakan Prewit Deteksi Tepi

%%Program Prewit

clear all,close all,clc

%A=input('masukkan gambar anda:\n');

A2=imread('harimau.jpg');

R=A2(:,:,1);

G=A2(:,:,2);

B=A2(:,:,3);

sobx=[-1 0 1; -1 0 1; -1 0 1];

soby=[1 1 1; 0 0 0; -1 -1 -1];

k=im2double(R);

[r,t]=size(k);

for(d=2:r-1);

    for(f=2:t-1);

        w0=k(d,f);

        w1=k(d,f+1);

        w2=k(d-1,f+1);

        w3=k(d-1,f);

        w4=k(d-1,f-1);

        w5=k(d,f-1);

        w6=k(d+1,f-1);

        w7=k(d+1,f);

        w8=k(d+1,f+1);

        p=[w4 w3 w2; w5 w0 w1; w6 w7 w8];

        px=(sum(sum(p.*sobx)))^2;

        py=(sum(sum(p.*soby)))^2;

        pz=sqrt(px+py);

        l1(d,f)=pz;

    end

end

k=im2double(G);

[r,t]=size(k);

for(d=2:r-1);

    for(f=2:t-1);

        w0=k(d,f);

        w1=k(d,f+1);

        w2=k(d-1,f+1);

        w3=k(d-1,f);

        w4=k(d-1,f-1);

        w5=k(d,f-1);

        w6=k(d+1,f-1);

        w7=k(d+1,f);

        w8=k(d+1,f+1);

        p=[w4 w3 w2; w5 w0 w1; w6 w7 w8];

        px=(sum(sum(p.*sobx)))^2;

        py=(sum(sum(p.*soby)))^2;

        pz=sqrt(px+py);

        l2(d,f)=pz;

    end

end

k=im2double(B);

[r,t]=size(k);

for(d=2:r-1);

    for(f=2:t-1);

        w0=k(d,f);

        w1=k(d,f+1);

        w2=k(d-1,f+1);

        w3=k(d-1,f);

        w4=k(d-1,f-1);

        w5=k(d,f-1);

        w6=k(d+1,f-1);

        w7=k(d+1,f);

        w8=k(d+1,f+1);

        p=[w4 w3 w2; w5 w0 w1; w6 w7 w8];

        px=(sum(sum(p.*sobx)))^2;

        py=(sum(sum(p.*soby)))^2;

        pz=sqrt(px+py);

        l3(d,f)=pz;

    end

end

q(:,:,1)=l1;

q(:,:,2)=l2;

q(:,:,3)=l3;

subplot(1,2,1), imshow (A2);

subplot(1,2,2), imshow (q), pixval on;