Matlab Syntax Summary before UTS

Reading an image (jpg, bmp, png, tif):

image = imread (‘image.ext’);

Showing an image (jpg, bmp, png, tif):

imshow (‘image.ext’);

Showing some of image in one figure/screen:

subplot (m,n,p); imread(‘img.ext’); %annotation: %m = total row %n = total column %p = image position

Making a new screen/figure:

figure;

Conversion from RGB to grayscale:

gray = rgb2gray(image);

Conversion from RGB to HSV:

hsv = rgb2hsv(image);

Conversion from RGB to black and white (BW):

bw = im2bw(image);

Looking for an image histogram:

histogram = imhist(image); %it can’t be implemented in RGB image plot(histogram);

Accessing pixel in certain position:

pixel = image (m,n);

Kernel prewitt:

-1 0 1 -1 0 1          %for left -1 0 1

1 0 -1 1 0 -1          %for right 1 0 -1

Kernel sobel:

-1 0 1 -2 0 2          %for left -1 0 1

1 0 -1 2 0 -2          %for right 1 0 -1

Kernel laplace:

-1 -1 -1 -1  8 -1         %trial 1 -1 -1 -1

1 -2  1 -2  4 -2         %trial 2  1 -2  1

Rotation:

function rotasi(img)     [row,col] = size(img);     for i = 1:row         for j = 1:col             out(j,row+1-i) = img(i,j);         end     end     subplot(1,2,1),imshow(img);     subplot(1,2,2),imshow(out); end %annotaion: %90 degrees = (j,row+1-i) %180 degrees = (row+1-i,column+1-j) %270 degrees = (column +1-j,i)

Translation:

function translasi(img,m,n)     row = size(img,1);     column = size(img,2);     for i = 1:row         for j = 1:column             if i+m>0 && i+m<row+1 && j-n>0 && j-n<column+1                 result(i,j) = img(i+m, j-n);             else                 result(i,j) = img(1,1)*0;             end         end     end     imshow(result); end

Dilatation:

function dilatasi(img,sx,sy)     row = size(img,1)*sx;     column = size(img,2)*sy;     for i = 1:row         for j = 1:column             if sx*i>0 && sx*i<row+1 && sy*j>0 && sy*j<column+1                 out(sx*i, sy*j) = img(i,j);             end         end         imshow(out);     end end %annotation: %sx = sy = scale

Reflection:

To binary (for grayscale only):

function result = toBiner(img)     result = img>=128; end

To negative (for grayscale only):

function result = toNegatif(img)     result = 255-img;     imshow(result); end

Brightening and darkening (for grayscale only):

function result = brightening(img, c)     result = img + c; end function result = darkening(img, c)     result = img - c; end

Clipping (for grayscale only):

function result = clipping(img)     out = img;        for i = size(img,1)         for j = size(img,2);             if img(i,j)<0                 out(i,j) = 0;             elseif img(i,j)>=0 && img(i,j)<=255                 out(i,j) = img(i,j);             else                 out(i,j) = 255;             end              end     end     result = out; end

Erotion (for binary only):

function result = erotion(img, a)     [maxRow, maxCol] = size(img);     out = img;     for i = 1:(maxRow-2)         for j = 1:(maxCol-2)             if img(i+1,j+1)==0                 for k = 1:3                     for l = 1:3                         out(i+k-1,j+l-1) = img(i+1,j+1).*a(k,l);                     end                 end             end         end     end     result = out; end %annotation: %a = matrix 3 x 3 (kernel that be used)

Dilation (for binary only):

function result = dilate(img,a)     [maxRow, maxCol] = size(img);     out = img;     for i = 1:(maxRow-2)         for j = 1:(maxCol-2)             if img(i+1,j+1)==1                 for k = 1:3                     for l = 1:3                         if a(k,l)==1                             out(i+k-1,j+l-1) = img(i+1,j+1).*a(k,l);                         end                     end                 end             end         end     end     result = out; end %annotation: %a = matrix 3 x 3 (kernel that be used)

Making mean filter for image:

function result = meanFilter(img)     a = [1/9 1/9 1/9;1/9 1/9 1/9;1/9 1/9 1/9];     [maxRow, maxCol] = size(img);     out = img;     for i = 1:(maxRow-2)         for j = 1:(maxCol-2)             if img(i+1,j+1)==0                 mean = 0;                 for k = 1:3                     for l = 1:3                         mean = mean + img(i+k-1,j+l-1).*a(k,l);                     end                 end                 out(i+1,j+1) = mean;             end         end     end     result = out; end

Making median filter for image:

function result = medianFilter(img)     [maxRow, maxCol] = size(img);     out = img;     for i = 1:(maxRow-2)         for j = 1:(maxCol-2)             if img(i+1,j+1)==0                 temp = zeros(1,9);                 for k = 1:3                     for l = 1:3                         temp(1,l+3*(k-1)) = img(i+k-1,j+l-1);                     end                 end                 out(i+1,j+1) = median(temp,2);             end         end     end     result = out; end

Making a chess board:

function chessBoard     [x,y] = meshgrid(0:1:255);     z = mod(floor(x/32)+floor(y/32),2);     imshow(z) end

Making a white hole:

function whiteHole(radius)     [x,y] = meshgrid(0:255,0:255);     img = (sqrt((x-127).^2 + (y-127).^2)<= radius);     imshow(img); end