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TRANSCRIPT
Chapter 1 Introduction
* What is Computer Vision?
* Applications
* Relations with other fields
* Resources
1.1 What is Computer Vision?
Computer vision is a field that includes methods
for acquiring, processing, analyzing, and
understanding one or more images from the real
world in order to produce and communicate
numerical or symbolic information to users or
other systems.
How to acquire images?
Why we want the computer to understand the images?
Why we need to process and analyze images?
1.2 Applications
Industrial inspection and quality control – detect
cracks in bottle
Reverse engineering – generate 3D object model
from images
Face/gesture recognition – security
Track and count humans – surveillance, human-
computer interaction
Track and count vehicles – road monitoring
Image database query – automatic image retrieval
Medical image analysis – assist diagnosis, surgery
1.3 Related disciplines
Computer
Vision
Image
Processing
noise filtering, edge detection, etc.
computer vision = machine vision = image understanding
Computer vision is, in some ways, the inverse
of computer graphics.
Many computer vision methods use and extend
signal processing techniques
Pattern recognition can be considered as part of
computer vision
original image 3D model synthetic image
CV CG
1.4 To know more about Computer Vision
1.4.1 conference
• International Conference on Computer Vision
(ICCV)
• International Conference on Computer Vision
and Pattern Recognition (CVPR)
• European Conference on Computer Vision
(ECCV)
1.4.2 journal
• International Journal of Computer Vision
• IEEE Transactions on Pattern Analysis and
Machine Intelligence
• Computer Vision and Image Understanding
• Machine Vision and Applications
1.4.3 internet
• CVonline
(http://homepages.inf.ed.ac.uk/rbf/CVonline)
• Numerical Recipes
(http://apps.nrbook.com/empanel/index.html#)
1.5 Overview of MATLAB
1.5.1 The MATLAB environment
• when you start MATLAB, the command window
will open with the prompt >>
• user can enter commands or data in the
command window
• for each command typed in, you get the result
immediately
• if you do not assign the result to a variable,
MATLAB will assign it to ans
1.5.2 Assignment
• assign value(s) to variable name(s)
scalar variable
>> a = 4
a =
4
>>
>> a = 4;
>>
>> a = 4, A = 6
a =
4
A =
6
>>
No echo printCase sensitive
Separate
multiple
commands by
comma
array
• a collection of values represented by one
variable name
• one-dimensional array – vector
• two-dimensional array – matrix
>> a = [1 2 3 4 5]
a =
1 2 3 4 5
>>
Row vector
>> a = [1;2;3;4;5]
a =
1
2
3
4
5
>>
>> a = [1 2 3 4 5]'
a =
1
2
3
4
5
>>
Column vector
Use single quote
as transpose
operator
>> A = [1 2 3; 4 5 6; 7 8 9]
A =
1 2 3
4 5 6
7 8 9
>>
>> A = [1 2 3
4 5 6
7 8 9]
A =
1 2 3
4 5 6
7 8 9
>>
Press Enter key
to separate the rows
To access individual element:
>> a(3)
ans =
3
>>
>> A(2,3)
ans =
6
>>Row index
Column index
colon operator
>> A(2,:)
ans =
4 5 6
>>
Access the entire row
>> t = 1:0.5:3
t =
1.0000 1.5000 2.0000 2.5000 3.0000
>>
start endincrement (If it is omitted,
the default value is 1)
>> t = 10:-1:5
t =
10 9 8 7 6 5
>>
negative increment
To extract part of the array:
>> t(2:4)
ans =
9 8 7
>>
1.5.3 Mathematical operations
^ exponentiation
- negation
* / multiplication, division
\ left division
+ - addition, subtraction
• priority order can be overridden with parentheses
Highest priority
Lowest priority
>> y = -4 ^ 2
y =
-16
>>
>> y = (-4) ^ 2
y =
16
>>
1.5.4 M-file
• M-file provides an alternative way of using
MATLAB to perform numerical analysis
• starts with the word function
• can have input argument(s) and output(s)
• multiple inputs - separate by comma
• multiple outputs – separate by comma,
enclose in square brackets
• it contains a series of statements
• the file is stored with an extension .m
function outvar = funcname(arglist)
% comments
statements
outvar = value;
outvar: name of output variable
funcname: name of function
arglist: argument list
comments: information for user
1.5.5 Structured programming
• simple M-file performs command sequentially,
from the first statement to the last
• the program is highly restrictive
• real programs usually have non-sequential
execution paths, which can be achieved via
decisions and loops
decision
• the branching of execution flow based on a
decision
if condition
statements
end
if condition
group 1 statements
else
group 2 statements
end
if condition 1
group 1 statements
elseif condition 2
group 2 statements
.
.
else
else statements
end
• one simple form of condition is a relational
expression that compares two values
value 1 relation value 2
operator relation
= = equal
~= not equal
< less than
> greater than
<= less than or equal to
>= greater than or equal to
• logical operators can be used to test more
than one logical condition
• there is priority order, use parentheses to
override it
operator meaning
~ not
&& and
|| or
Highest priority
Lowest priority
loop
• the repetition of a group of statements
for index = start:step:finish
statements
end
for i = 1:2:5
disp(i)
end
for i = 5:-2:1
disp(i)
end
for i = 1:5
disp(i)
end
Positive step
Negative step
Default step = 1
while condition
statements
end
i = 5;
while i > 0
i = i – 1;
disp(i)
end
Summary
♦ scope of Computer Vision
♦ application areas
♦ relations with other fields
♦ resources and development platform of
computer vision