1. CSE107 Matlab Introduction

2. Matlab programming language and software development environment
Matlab Image Processing Toolbox (IPT)

3. Matlab overview High performance language for technical computing
Matlab = “matrix laboratory”
Array based – very linear-algebra like
Made by MathWorks

4. Matlab overview Not cheap – academic prices ~$500/seat
Student version available
Free from UC Merced IT?
Fully functional (?)
Simulink
Simulation and Model-Based Design
Graphical tool for connecting modules in a work-flow type environment
Open source alternative
Octave is a free computer program for performing numerical computations which is mostly compatible with MATLAB (source: Wikipedia)

5. Matlab overview Advantages Disadvantages
Lots of built-in functionality especially via toolboxes
Math-like
Good visualization
Good for learning and prototyping
Disadvantages
Can be slow
Not free

6. Matlab overview
Let’s take a look…
Starting Matlab
Windows
Linux

7. Matlab overview Matlab desktop Command Window Workspace Browser
Current Directory
Command History Windows
One or more Figure Windows

8. Matlab overview Matlab is a scripting language – interpreted
Interactive
Can type commands in Command Window
Can run scripts (.m files) ~ programs
Functions also stored in .m files

9. Matlab overview Editing .m files Matlab editor Any text editor
Graphical
Debugging
Any text editor

10. Matlab overview Matlab help Graphical Text MathWorks website
Help->Matlab Help
doc <function>
Text
help <function>
lookfor <keyword> -all
MathWorks website

11. Matlab overview
Can save/load workspaces and variables

12. Matlab overview Defining/declaring variables who whos Comments
The semicolon (;)
clear [all]

13. Matlab overview .m files containing scripts
Running .m files – just type name
Search path for .m files
File->Set path
Editing .m files: edit <filename.m>
Debugging

14. Matlab overview
intro.m

15. Matlab overview – data types
© 2004 R. C. Gonzalez, R. E. Woods, and S. L. Eddins

16. Matlab overview – data types
Converting between data types
Ex: a = uint8(b)
Double->uint8
Values < 0 mapped to 0
Values > 255 mapped to 255
Fractions discarded
Be aware of this!

17. Matlab overview - vectors
1xN dimensional array is called a row vector
Index of first element is 1 (not 0)
Initialize using square brackets
>> v = [ ]
v =
>> v(2)
ans = 3

18. Matlab overview - vectors
Convert row vector to column vector and vice versa using transpose operator (‘)
>> w = v'
w = 1 3 5 7 9

19. Matlab overview - vectors
To access blocks of elements, use colon (:) notation
>> v(1:3)
ans =
>> v(3:end)

20. Matlab overview - vectors
Indexing not restricted to contiguous elements
>> v(1:2:5)
ans =
>> v(5:-2:1)

21. Matlab overview - vectors
Colon by itself returns column vector
>> v(:)
ans = 1 3 5 7 9

22. Matlab overview - vectors
Can index into a vector using a vector
>> v([1 4 5])
ans =

23. Matlab overview - matrices
Matrices can be initialized as sequence of row vectors separated by semicolons (;)
>> A = [1 2 3; 4 5 6; 7 8 9]
A =

24. Matlab overview - matrices
Index into matrices using two indices
>> A(2,3)
ans = 6

25. Matlab overview - matrices
Use colon to select rows and columns
>> C3 = A(:,3)
C3 = 3 6 9
>> R2 = A(2,:)
R2 =

26. Matlab overview - matrices
Use colon to select blocks
>> T2 = A(1:2, 1:3)
T2 =

27. Matlab overview - matrices
Can also use colon for assignment
>> B = A;
>> B(:,3) = 0
B =

28. Matlab overview - matrices
Can index using logical data types
>> D = logical([1 0 0; 0 0 1; 0 0 0])
D =
>> A(D)
ans = 1 6

29. Matlab overview - matrices
Can use comparison operators to index
>> A(B==0)
ans = 3 6 9
>> E = (B==0)
E =
>> whos E
Name Size Bytes Class
E x double array (logical)
Grand total is 9 elements using 72 bytes

30. Matlab overview - matrices
Use find function to determine indices of values satisfying condition
>> [i,j] = find(B~=0);
>> i'
ans =
>> j'

31. Matlab overview - matrices
Use ndims to find dimension
>> d = ndims(A)
d = 2

32. Matlab overview - matrices
Use size to find sizes of dimensions
>> size(T2)
ans =
>> size(T2,1) 2
>> size(T2,2) 3

33. Matlab overview - matrices
Can specify dimension for many functions
>> sum(T2)
ans =
>> sum(T2,1)
>> sum(T2,2) 6 15

34. Matlab overview - matrices
Can recurse to compute over all dimensions
>> sum(sum(T2))
ans = 21

35. Matlab overview – standard arrays
zeros(M,N) -> MxN matrix of zeros of type double
ones(M,N) -> MxN matrix of ones of type double
rand(M,N) -> MxN matrix of uniformly distributed random numbers in the interval [0,1]
randn(M,N) -> MxN matrix of normally (Gaussian) distributed random numbers with mean 0 and variance 1

36. Matlab overview – standard arrays
>> A = 5*ones(3,3)
A =
>> B = rand(2,4)
B =

37. Matlab overview - .m file programming Operators
3 types of operators
Arithmetic operators that perform numeric computations
Relational operators that compare operands quantitatively
Logical operators that perform the functions AND, OR, and NOT

38. Arithmetic operators I
© 2004 R. C. Gonzalez, R. E. Woods, and S. L. Eddins

39. Arithmetic operators II
© 2004 R. C. Gonzalez, R. E. Woods, and S. L. Eddins

40. Relational operators
© 2004 R. C. Gonzalez, R. E. Woods, and S. L. Eddins

41. Matlab overview - .m file programming Relational operators
>> B = [0 2 4; 3 5 6; 3 4 9]
B =
>> A == B
ans =

42. Important variables and constants
© 2004 R. C. Gonzalez, R. E. Woods, and S. L. Eddins

43. Flow control statements
© 2004 R. C. Gonzalez, R. E. Woods, and S. L. Eddins

44. IPT overview: digital image representation
What’s the difference?
© 2004 R. C. Gonzalez, R. E. Woods, and S. L. Eddins

45. IPT overview: images as matrices
images as functions:
images as matrices:

46. IPT overview: reading images
Use imread() to read images from file
help imread
>> f = imread('hong_kong.jpg');
>> size(f)
ans =
>> whos f
Name Size Bytes Class
f x uint8 array
Grand total is elements using bytes
>> f(1,1) 38
>> f

47. IPT overview: reading images
© 2004 R. C. Gonzalez, R. E. Woods, and S. L. Eddins

48. IPT overview: displaying images
Use imshow() to display images
help imshow
>> imshow(f)
>> imshow(f,[50 100])
Be careful about the dataype of f!

49. IPT overview: more on imshow
help imshow
IMSHOW Display image in Handle Graphics figure.
IMSHOW(I) displays the grayscale image I.
IMSHOW(I,[LOW HIGH]) displays the grayscale image I, specifying the display
range for I in [LOW HIGH]. The value LOW (and any value less than LOW)
displays as black, the value HIGH (and any value greater than HIGH) displays
as white. Values in between are displayed as intermediate shades of gray,
using the default number of gray levels. If you use an empty matrix ([]) for
[LOW HIGH], IMSHOW uses [min(I(:)) max(I(:))]; that is, the minimum value in
I is displayed as black, and the maximum value is displayed as white.
IMSHOW(RGB) displays the truecolor image RGB.
IMSHOW(BW) displays the binary image BW. IMSHOW displays pixels with the
value 0 (zero) as black and pixels with the value 1 as white.
IMSHOW(X,MAP) displays the indexed image X with the colormap MAP.

50. IPT overview: displaying images
Use impixelinfo to examine pixel values in currently displayed image
help impixelinfo
figure – Open new figure window
close all – Close all figure windows

51. IPT overview: writing images
Use imwrite to write images to file
help imwrite
Use imfinfo to get information about image file
help imfinfo
Use File->Export to save a figure to file
Can also save figure using command
print –fno –dformat –rres filename

52. IPT overview: image types
IPT supports four types of images
Intensity images (“grayscale”)
Binary images (“black and white”)
Indexed images (color)
RGB images (color)

53. IPT overview: converting between image types
Be careful about how ranges are mapped: [0,255]  [0,1]
© 2004 R. C. Gonzalez, R. E. Woods, and S. L. Eddins

54. IPT overview: converting between image types
>> h = uint8([25 50; ]);
>> g = im2double(h);
>> g
g =
>> f = double([ ; ]);
>> g = im2uint8(f);
>> g
g =

55. Matlab overview - .m file programming Code optimization – preallocating arrays
Preallocating arrays: use zeros() for example
for x=1:M
f(x) = A * sin((x-1)/(2*pi));
end or
f = zeros(M,1); % preallocate the array
for x=1:M
f(x) = A * sin((x-1)/(2*pi));
end

56. Matlab overview - .m file programming Code optimization – preallocating arrays
sin_no_preallocate.m
sin_preallocate.m

57. Matlab overview - .m file programming Code optimization – preallocating arrays
Improves code execution time
Helps reduce memory fragmentation

58. Matlab overview - .m file programming Code optimization – vectorizing loops
Vectorizing loops: converting for and while loops to equivalent vector or matrix operations.
for x=1:M
f(x) = A * sin((x-1)/(2*pi));
end or
x = 0:M-1;
f = A * sin(x/(2*pi));

59. Matlab overview - .m file programming Code optimization
sin_loop.m
sin_vectorize.m

60. Matlab overview - .m file programming Interactive output I
disp(argument)
>> A = [1 2; 3 4];
>> disp(A);
>> sc = 'Digital Image Processing';
>> disp(sc);
Digital Image Processing

61. Matlab overview - .m file programming Interactive output II
fprintf(1,’format’,argument);
>> x = 5;
>> fprintf(1,'x = %.5f',x);
x =
>> fprintf(1,'x = %e',x);
x = e+000

62. Matlab overview - .m file programming Interactive input
t = input(‘message’, ‘s’)
>> t = input('Enter you data: ','s');
Enter you data: 1,2,4
>> disp(t)
1,2,4
>> class(t)
ans =
char
>> size(t)
>> n=str2num(t)
n =
>> class(n)
double
>> size(n)

63. Matlab overview - .m file programming Plotting
help plot
plot_example.m

64. Matlab overview - .m file programming Cell arrays
Cell array: multidimensional array whose elements are copies of other arrays
Allows you to mix datatypes
>> c = {'gauss', [1 0; 0 1], 3}
c =
'gauss' [2x2 double] [3]
>> c{1}
ans =
gauss
>> c{2}
>> c{3} 3

65. Matlab overview - .m file programming Structures
Structures: similar to cell arrays except addressed by fields
>> S.char_string = 'gauss';
>> S.matrix = [1 0; 0 1];
>> S.scalar = 3;
>> S
S =
char_string: 'gauss'
matrix: [2x2 double]
scalar: 3
>> S.matrix
ans =