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CS100: Into to Computer Science. Image Processing in MatLab. MatLab is a powerful tool to manipulate graphics and images. Prepared by Fred Annexstein University of Cincinnati Some Rights Reserved. WORKING WITH IMAGES in MatLab. Basic Image functions: Reading: img1=imread('image1.jpg');

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image processing in matlab

CS100: Into to Computer Science

Image Processing in MatLab

MatLab is a powerful tool to manipulate graphics and images

Prepared by Fred Annexstein

University of Cincinnati

Some Rights Reserved

slide2

WORKING WITH IMAGES in MatLab

Basic Image functions:

Reading:

img1=imread('image1.jpg');

Writing:

imwrite(img1, 'image2.jpg');

Displaying:

imshow(img1);

Recall that Last time we did an Exercise: Find 2 images online and add them together.

You only needed to crop them to the same size.

slide3

WORKING WITH IMAGES in MatLab

RESIZING

>> img=imread(‘my.jpg');

>> [rows, cols, colors]= size(img)

% Increase the number of rows

>> stretchfactor = 1.5

>> rowVec= linspace(1,rows,stretchfactor*rows);

>> newrows=round(rowVec);

% Decrease number of columns

>> stretchfactor = 0.75;

>> colVec= linspace(1,cols,stretchfactor*cols);

>> newcols=round(colVec);

>> newimag=img(newrows,:,:)

>> imshow(newimg);

>> newimag=newimg(:,newcols,:)

>>imshow(newimg)

slide4

WORKING WITH IMAGES in MatLab

  • Color Masking
  • Sometimes we want to replace pixels of an image of one or more colors with pixels from another image. It is useful to use a “blue screen” in some instances.
  • Find an image with a big plot of one color. First we will replace that color. And then we will find another image for pixel replacement.
  • Let us plot the color values of one chosen row…This will tell us the pixel values of the color we want to replace.
  • v = imread(‘myimg.jpg’)
  • image(v)
  • row= input(‘which row?’);
  • red = v(row,:,1);
  • green = v(row,:,2);
  • blue = v(row,:,3);
  • plot(red,’r’);
  • hold on
  • plot(green,’g’);
  • plot(blue,’b’);
slide5

WORKING WITH IMAGES in MatLab

  • Suppose we want to replace those values whose intensities exceed a threshold value of 160 in each color.
  • v= imread(‘myimg.jpg’);
  • thresh= 160
  • layer = (v(:,:,1) > thresh) & (v(:,:,2) > thresh) (v(:,:,2) > thresh)
  • mask(:,:,1) = layer;
  • mask(:,:,2) = layer;
  • mask(:,:,3) = layer;
  • If you want to only mask a portion of the image you can use something like…
  • >> mask(700:end,:,:)= false;
  • Which sets the mask so that we do not affect rows 700 and above
  • To reset the color to red
  • >>newv = v;
  • >>newv(mask)(1) = 255
  • Or to replace pixels from a different image w use…>> newv(mask) = w(mask);
  • Let us try to do this with a blue screen…..