MATLAB & Image Processing

MATLAB WORKSHOP

 FOR
EE, ECE, CS, Geophysics, B
ioinformatics, Mechanical
Engineering

Outline

• Introduction to MATLAB
– Basics & Examples

• Image Processing with MATLAB

What is MATLAB?
• MATLAB = Matrix Laboratory

• “MATLAB is a high-level language and
interactive environment that enables you to
perform computationally intensive tasks faster
than with traditional programming languages
such as C, C++ and Fortran.”
(www.mathworks.com)

• MATLAB is an interactive, interpreted language
that is designed for fast numerical matrix
calculations

The MATLAB Environment
• MATLAB window
components:
Workspace
> Displays all the defined
variables
Command Window
> To execute commands
in the MATLAB
environment
Command History
> Displays record of the
commands used
File Editor Window
> Define your functions

MATLAB Help
• MATLAB Help is an
extremely powerful
assistance to learning
MATLAB

• Help not only contains the
theoretical
background, but also
shows demos for
implementation

• MATLAB Help can be
opened by using the
HELP pull-down menu

MATLAB Help (cont.)
• Any command description
can be found by typing
the command in the
search field

• As shown above, the
command to take square
root (sqrt) is searched

• We can also utilize
MATLAB Help from the
command window as
shown

More about the Workspace
• who, whos – current variables in the
workspace
• save – save workspace variables to *.mat
file
• load – load variables from *.mat file
• clear – clear workspace variables

- CODE

Matrices in MATLAB
• Matrix is the main MATLAB data type
• How to build a matrix?
– A=[1 2 3; 4 5 6; 7 8 9];
– Creates matrix A of size 3 x 3
• Special matrices:
– zeros(n,m), ones(n,m), eye(n,m), r
and(), randn()

Basic Operations on Matrices
• All operators in MATLAB are defined on
matrices: +, -
, *, /, ^, sqrt, sin, cos, etc.
• Element-wise operators defined with a
preceding dot: .*, ./, .^
• size(A) – size vector
• sum(A) – columns’ sums vector
• sum(sum(A)) – sum of all the elements
- CODE

Variable Name in Matlab
• Variable naming rules
- must be unique in the first 63 characters
- must begin with a letter
- may not contain blank spaces or other types of punctuation
- may contain any combination of letters, digits, and
underscores
- are case-sensitive
- should not use Matlab keyword
• Pre-defined variable names
• pi

Logical Operators

• ==, <, >, (not equal) ~=, (not) ~

• find(‘condition’) – Returns indexes
of A’s elements that satisfy the condition

Logical Operators (cont.)
• Example:
>>A=[7 3 5; 6 2 1], Idx=find(A<4)
A=
7 3 5
6 2 1
Idx=
3
4
6

Flow Control
• MATLAB has five flow control constructs:
– if statement
– switch statement
– for loop
– while loop
– break statement

if
• IF statement condition
– The general form of the IF statement is
IF expression
statements
ELSEIF expression
statements
ELSE
statements
END

switch
• SWITCH – Switch among several cases based
on expression
• The general form of SWITCH statement is:
SWITCH switch_expr
CASE case_expr,
statement, …, statement
CASE {case_expr1, case_expr2, case_expr3, …}
…
OTHERWISE
END

switch (cont.)
• Note:
– Only the statements between the matching
CASE and the next CASE, OTHERWISE, or END
are executed
– Unlike C, the SWITCH statement does not fall
through (so BREAKs are unnecessary)

for
• FOR repeats statements a specific
number of times

• The general form of a FOR statement is:
FOR variable=expr
statements
END

Code
 Assume k has already been assigned a value.
Create the Hilbert matrix, using zeros to
preallocate the matrix to conserve memory:
a = zeros(k,k) % Preallocate matrix
for m = 1:k
for n = 1:k
a(m,n) = 1/(m+n -1);
end
end

while
• WHILE repeats statements an indefinite
number of times
• The general form of a WHILE statement is:
WHILE expression
statements
END

Scripts and Functions
• There are two kinds of M-files:

– Scripts, which do not accept input arguments
or return output arguments. They operate on
data in the workspace

– Functions, which can accept input arguments
and return output arguments. Internal
variables are local to the function

Functions in MATLAB (cont.)
• Example:
– A file called STAT.M:
function [mean, stdev]=stat(x)
%STAT Interesting statistics.
n=length(x);
mean=sum(x)/n;
stdev=sqrt(sum((x-mean).^2)/n);
– Defines a new function called STAT that calculates
the mean and standard deviation of a vector. Function
name and file name should be the SAME!

Visualization and Graphics
• plot(x,y),plot(x,sin(x)) – plot 1D function
• figure, figure(k) – open a new figure
• hold on, hold off – refreshing
• axis([xmin xmax ymin ymax]) – change axes
• title(‘figure titile’) – add title to figure
• mesh(x_ax,y_ax,z_mat) – view surface
• contour(z_mat) – view z as topo map
• subplot(3,1,2) – locate several plots in figure

Saving your Work
• save mysession
% creates mysession.mat with all variables
• save mysession a b
% save only variables a and b
• clear all
% clear all variables
• clear a b
% clear variables a and b
• load mysession
% load session

What is the Image Processing Toolbox?

• The Image Processing Toolbox is a collection of
functions that extend the capabilities of the MATLAB’s
numeric computing environment. The toolbox supports a
wide range of image processing operations, including:
– Geometric operations
– Neighborhood and block operations
– Linear filtering and filter design
– Transforms
– Image analysis and enhancement
– Binary image operations
– Region of interest operations

Images in MATLAB
• MATLAB can import/export • Data types in MATLAB
several image formats: – Double (64-bit double-precision
– BMP (Microsoft Windows floating point)
Bitmap) – Single (32-bit single-precision
– GIF (Graphics Interchange floating point)
Files) – Int32 (32-bit signed integer)
– HDF (Hierarchical Data Format) – Int16 (16-bit signed integer)
– JPEG (Joint Photographic – Int8 (8-bit signed integer)
Experts Group) – Uint32 (32-bit unsigned integer)
– PCX (Paintbrush) – Uint16 (16-bit unsigned integer)
– PNG (Portable Network – Uint8 (8-bit unsigned integer)
Graphics)
– TIFF (Tagged Image File
Format)
– XWD (X Window Dump)
– raw-data and other types of
image data

Images in MATLAB
• Binary images : {0,1}
• Intensity images : [0,1] or uint8, double etc.
• RGB images : m × n × 3
• Multidimensional images: m × n × p (p is the number of layers)

Image Import and Export
• Read and write images in Matlab
img = imread('apple.jpg');
dim = size(img);
figure;
imshow(img);
imwrite(img, 'output.bmp', 'bmp');

• Alternatives to imshow
imagesc(I)
imtool(I)
image(I)

Images and Matrices
[0, 0]
How to build a matrix
(or image)? o
Intensity Image:

Row 1 to 256
row = 256;
col = 256;
img = zeros(row, col);
img(100:105, :) = 0.5;
img(:, 100:105) = 1;
figure;
o
imshow(img);
Column 1 to 256
[256, 256]

Images and Matrices
Binary Image:

row = 256;
col = 256;
img = rand(row,
col);
img = round(img);
figure;
imshow(img);

Image Display
• image - create and display image object
• imagesc - scale and display as image
• imshow - display image
• colorbar - display colorbar
• getimage - get image data from axes
• truesize - adjust display size of image
• zoom - zoom in and zoom out of 2D plot

Image Conversion
• gray2ind - intensity image to index image
• im2bw - image to binary
• im2double - image to double precision
• im2uint8 - image to 8-bit unsigned integers
• im2uint16 - image to 16-bit unsigned integers
• ind2gray - indexed image to intensity image
• mat2gray - matrix to intensity image
• rgb2gray - RGB image to grayscale
• rgb2ind - RGB image to indexed image

Image Operations
• RGB image to gray image
• Image resize
• Image crop
• Image rotate
• Image histogram
• Image histogram equalization
• Image DCT/IDCT
• Convolution

Outline

• Introduction to MATLAB
• Image Processing with MATLAB

Examples working with Images
(1/2)
Blending two images

Examples working with Images
(2/2)
Sobel descriptor to detect object edge

Performance Issues
• The idea: MATLAB is
– very fast on vector and matrix operations
– Correspondingly slow with loops

• Try to avoid loops
• Try to vectorize your code
http://www.mathworks.com/support/tech-
notes/1100/1109.html

Vectorize Loops
• Example
– Given image matrices, A and B, of the same size (540*380), blend
these two images
apple = imread(‘apple.jpg');
orange = imread(‘orange.jpg’);
• Poor Style
% measure performance using stopwatch timer
tic
for i = 1 : size(apple, 1)
for j = 1 : size(apple, 2)
for k = 1 : size(apple, 3)
output(i, j, k) = (apple(i, j, k) +
orange(i, j, k))/2;
end
end
end
toc
• Elapsed time is 0.138116 seconds

Vectorize Loops (cont.)
• Example
– Given image matrices, A and B, of the same size (600*400), blend
these two images
apple = imread(‘apple.jpg');
orange = imread(‘orange.jpg’);

• Better Style
tic % measure performance using stopwatch timer
Output = (apple + orange)/2;
toc
• Elapsed time is 0.099802 seconds

• Computation is faster!

THE END

• Thanks for your attention! 

• Questions?

MATLAB & Image Processing

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