Computer vision involves acquiring, processing, analyzing and understanding images and video to extract numerical or symbolic information. It has applications in industrial inspection, medical imaging, surveillance, and more. It is related to fields like image processing, pattern recognition and computer graphics. MATLAB is a common platform used for computer vision development, allowing image processing, algorithms, and structured programming.

1. Chapter 1 Introduction
* What is Computer Vision?
* Applications
* Relations with other fields
* Resources

2. 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 need to process and analyze images?
Why we want the computer to understand the images?

3. 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

4. 1.3 Related disciplines
computer vision = machine vision = image understanding
Computer Image
Vision Processing
noise filtering, edge detection, etc.

5. Many computer vision methods use and extend
signal processing techniques
Pattern recognition can be considered as part of
computer vision
Computer vision is, in some ways, the inverse
of computer graphics.
CV CG
original image 3D model synthetic image

6. 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)

7. 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#)

8. 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

11. 1.5.2 Assignment
• assign value(s) to variable name(s)
scalar variable
>> a = 4 >> a = 4, A = 6
a= a=
4 4 Separate
>> A= multiple
6 commands by
>> a = 4; >> comma
>>
Case sensitive
No echo print

12. 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
>>

13. >> a = [1;2;3;4;5] >> a = [1 2 3 4 5]'
a= a=
1 1 Use single quote
2 2 as transpose
3 3 operator
4 4
5 5
>> >>
Column vector

14. >> A = [1 2 3; 4 5 6; 7 8 9] >> A = [1 2 3
A= 456
1 2 3 7 8 9]
4 5 6 A=
7 8 9 1 2 3
>> 4 5 6
7 8 9
>>
Press Enter key
to separate the rows

15. To access individual element:
>> a(3)
ans =
3
>>
>> A(2,3)
ans = Column index
6 Row index
>>

16. colon operator
>> A(2,:)
ans =
4 5 6
>>
Access the entire row
increment (If it is omitted,
start end the default value is 1)
>> t = 1:0.5:3
t=
1.0000 1.5000 2.0000 2.5000 3.0000
>>

17. negative increment
>> t = 10:-1:5
t=
10 9 8 7 6 5
>>
To extract part of the array:
>> t(2:4)
ans =
9 8 7
>>

18. 1.5.3 Mathematical operations
^ exponentiation Highest priority
- negation
*/ multiplication, division
left division
+- addition, subtraction Lowest priority
• priority order can be overridden with parentheses

19. >> y = -4 ^ 2
y=
-16
>>
>> y = (-4) ^ 2
y=
16
>>

20. 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

21. function outvar = funcname(arglist)
% comments
statements
outvar = value;
outvar: name of output variable
funcname: name of function
arglist: argument list
comments: information for user

28. 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

29. decision
• the branching of execution flow based on a
decision
if condition if condition 1
statements group 1 statements
end elseif condition 2
group 2 statements
if condition .
group 1 statements .
else else
group 2 statements else statements
end end

30. • 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

31. • logical operators can be used to test more
than one logical condition
• there is priority order, use parentheses to
override it
operator meaning
~ not Highest priority
&& and
|| or Lowest priority

32. loop
• the repetition of a group of statements
for index = start:step:finish
statements
end

33. for i = 1:2:5
disp(i) Positive step
end
for i = 5:-2:1
disp(i) Negative step
end
for i = 1:5
disp(i) Default step = 1
end

34. while condition
statements
end
i = 5;
while i > 0
i = i – 1;
disp(i)
end

38. Summary
♦ scope of Computer Vision
♦ application areas
♦ relations with other fields
♦ resources and development platform of
computer vision