The document describes the Image Processing Toolbox in MATLAB. It provides functions for reading, displaying, manipulating and writing images. Some key functions include imread to read an image, imshow to display it, imhist for histograms, imadjust for contrast adjustment, and imwrite to write the image. Operations like morphological opening, thresholding, labeling connected components and measuring object properties are also covered.

1. MATLAB
Image Processing Toolbox

2. Introduction
 Collection of functions (MATLAB
files) that supports a wide range of image
processing operations
 Documentation
 www.mathworks.com

3. Read an Image
 Read in an image
 Validates the graphic format
(bmp, hdf, jpeg, pcx, png, tiff, xwd)
 Store it in an array
clear, close all
I = imread(‘pout.tif`);
[X, map] = imread(‘pout.tif’);

4. Display an Image
imshow(I)

5. Check the Image in Memory
 < Name, Size, Bytes, Class >
whos
Name
Size
Bytes Class
ans 291x240
69840 uint8 array
Grand total is 69840 elements using 69840 bytes
uint8
uint16
double
[0, 255]
[0, 65535]
[0, 1]

6. Histogram Equalization
 Histogram: distribution of intensities
figure, imhist(I)
 Equalize Image (contrast)
I2 = histeq(I);
figure, imshow(I2)
figure, imhist(I2)

7. Histogram Equalization
(cont.)

8. Histogram Equalization
(cont.)

9. Write the Image
 Validates the extension
 Writes the image to disk
imwrite(I2, ’pout2.png’);
imwrite(I2, ‘pout2.png’, ‘BitDepth’, 4);

10. Morphological Opening
 Remove objects that cannot completely
contain a structuring element
 Estimate background illumination
clear, close all
I = imread(‘rice.tif’);
imshow(I)
background = imopen(I, strel(‘disk’, 15));
imshow(background)

11. Morphological Opening
(cont.)

12. Subtract Images
 Create a more uniform background
I2 = imsubtract(I, background);
figure, imshow(I2)

13. Adjust the Image Contrast
 stretchlim computes [low hight] to be
mapped into [bottom top]
I3 = imadjust(I2, stretchlim(I2), [0 1]);
figure, imshow(I3)

14. Apply Thresholding
to the Image
 Create a binary thresholded image
1.
2.
Compute a threshold to convert the intensity
image to binary
Perform thresholding creating a logical matrix
(binary image)
level = graythresh(I3);
bw = im2bw(I3, level);
figure, imshow(bw)

15. Apply Thresholding
to the Image (cont.)

16. Labeling Connected
Components
 Determine the number of objects in the
image
 Accuracy
(size of objects, approximated background,
connectivity parameter, touching objects)
[labeled, numObjects] = bwlabel(bw, 4);
numObjects
{= 80}
max(labeled(:))

17. Select and Display
Pixels in a Region
 Interactive selection
grain = imcrop(labeled)
 Colormap creation function
RGB_label = label2rgb(labeled,
@spring, ‘c’, ‘shuffle’);
imshow(RGB_label);
rect = [15 25 10 10];
roi = imcrop(labeled, rect)

18. Object Properties
 Measure object or region properties
graindata = regionprops(labeled, ‘basic’)
graindata(51).Area
{296}
graindata(51).BoundingBox
{142.5 89.5 24.0 26.0}
graindata(51).Centroid
{155.3953 102.1791}
 Create a vector which holds just one property for
each object
allgrains = [graindata.Area];
whos

19. Statistical Properties
of Objects
max(allgrains)
{ 695 }
 Return the component label of a grain size
biggrain = find(allgrains == 695) { 68 }
 Mean grain size
mean(allgrains)
 Histogram (#bins)
hist(allgrains, 20)
{ 249 }

20. Statistical Properties
of Objects (cont.)

21. Storage Classes
 double (64-bit), uint8 (8-bit), and uint16
(16-bit)
 Converting (rescale or offset)
double
im2double (automatic rescale and offsetting)
RGB2 = im2uint8(RGB1);
im2uint16
imapprox (reduce number of colors: indexed images)

22. Image Types
 Index
 Data
matrix (uint8, uint16, double)
 Colormap matrix (m x 3 array of double [0 1])
 Intensity (black = 0, white = ∞)
 Binary (0, 1)
B = logical(uint8(round(A))); (logical flag on)
B = +A; (logical flag off)
 RGB (m x n x 3 of truecolor)

23. Converting Image Types





dither
gray2ind
grayslice
im2bw
ind2gray




ind2rgb
mat2gray
rgb2gray
rgb2ind

24. Multiframe Image Arrays
 Same size, #planes, colormap
 Store separate images into one multiframe
array
A = cat(4, A1, A2, A3, A4, A5)
 Extract frames from a multiframe array
FRM3 = MULTI(:, :, :, 3)
 Display a frame
imshow(MULTI(:, :, :, 7))

25. Image Arithmetic




imabsdiff
imadd
imcomplement
imdivide
 imlincomb
 immultiply
 imsubtract

26. Adding Images
I = imread(‘rice.tif’);
J = imread(‘cameraman.tif’);
K = imadd(I, J);
imshow(K)
 Brighten an image results saturation
RGB = imread(‘flowers.tif’);
RGB2 = imadd(RGB, 50);
subplot(1, 2, 1); imshow(RGB);
subplot(1, 2, 2); imshow(RGB2);

27. Adding Images (cont.)

28. Adding Images (cont.)

29. Subtracting Images
 Background of a scene
rice = imread(‘rice.tif’);
background = imopen(rice, strel(‘disk’, 15));
rice2 = imsubtract(rice, background);
imshow(rice), figure, imshow(rice2);
 Negative values
imabsdiff

30. Subtracting Images (cont.)

31. Multiplying Images
 Scaling: multiply by a constant
 (brightens
>1, darkens <1)
 Preserves relative contrast
I = imread(‘moon.tif’);
J = immultiply(I, 1.2);
imshow(I);
figure, imshow(J)

32. Multiplying Images (cont.)

33. Dividing Images (Ratioing)
I = imread(‘rice.tif’);
background = imopen(I, strel(‘disk’, 15));
Ip = imdivide(I, background);
imshow(Ip, [])
 Linear combination only truncates the final
result
K = imlincomb(.5, I, .5, I2);

34. Dividing Images (cont.)

35. Coordinate Systems
 Pixel Coordinates



Discrete unit (integer)
(r, c)
 = (1, 1)
123
 Spatial Coordinates



Continuous unit
(x, y)
= (0.5, 0.5)

36. Non-default Spatial
Coordinate System
A = magic(5);
x = [19.5 23.5];
y = [8.0 12.0];
image(A, ‘xData’, x, ‘yData’, y), axis image,
colormap(jet(25))

37. Spatial Transformations
 Map pixel locations in an input image to
new locations in an output image



Resizing
Rotation
Cropping

38. Resizing Images
 Change the size of an image
I = imread(‘ic.tif’);
J = imresize(I, 1.25);
K = imresize(I, [100 150]);
figure, imshow(J)
figure, imshow(K)

39. Resizing Images (cont.)

40. Rotating Images
 Rotate an image by an angle in degrees
I = imread(‘ic.tif’);
J = imrotate(I, 35, ‘bilinear’);
imshow(I)
figure, imshow(J)

41. Rotating Images (cont.)

42. Cropping Images
 Extract a rectangular portion of an image
imshow ic.tif
I = imcrop;