introduction to digital images, their representations and types

1. Image Processing
Lecture 1
Introduction and Application

2. Image Formation
f(x,y) = reflectance(x,y) * illumination(x,y)
Reflectance in [0,1], illumination in [0,inf]

3. Sampling and Quantization

4. Sampling and Quantization

5. What is an image?
 We can think of an image as a function, f, from R2 to R:
 f( x, y ) gives the intensity at position ( x, y )
 Realistically, we expect the image only to be defined over a
rectangle, with a finite range:
 f: [a,b]x[c,d]  [0,1]
 A color image is just three functions pasted together.
We can write this as a “vector-valued” function:
( , )
( , ) ( , )
( , )
r x y
f x y g x y
b x y
 
 

 
 
 

6. Images as functions

7. What is a digital image?
 We usually operate on digital (discrete) images:
 Sample the 2D space on a regular grid
 Quantize each sample (round to nearest integer)
 If our samples are D apart, we can write this as:
f[i ,j] = Quantize{ f(i D, j D) }
 The image can now be represented as a matrix of integer values

8. Image processing
 An image processing operation typically defines a
new image g in terms of an existing image f.
 We can transform either the range of f.
 Or the domain of f:
 What kinds of operations can each perform?

9. Image Enhancement

10. Contrast Streching

11. Image Histograms

12. Histogram Equalization

13. Neighborhood Processing (filtering)
 Q: What happens if I reshuffle all pixels within
the image?
 A: It’s histogram won’t change. No point
processing will be affected…
 Need spatial information to capture this.

14. Programming Assignment #1
 Easy stuff to get you started with
Matlab
 Shobhit will hold your first tutorial
 Topics will be from next 2 lectures

15. Applications
&
Research Topics

16. Document Handling

17. Signature Verification

18. Biometrics

19. Fingerprint Verification / Identification

20. Fingerprint Identification Research at
UNR
Minutiae Matching
Delaunay Triangulation

21. Object Recognition

22. Object Recognition Research
reference view 1 reference view 2
novel view recognized

23. Indexing into Databases
 Shape content

24. Indexing into Databases (cont’d)
 Color, texture

25. Target Recognition
 Department of Defense (Army, Airforce,
Navy)

26. Interpretation of aerial photography is a problem domain in both
computer vision and registration.
Interpretation of Aerial Photography

27. Autonomous Vehicles
 Land, Underwater, Space

28. Traffic Monitoring

29. Face Detection

30. Face Recognition

31. Face Detection/Recognition Research at
UNR

32. Facial Expression Recognition

33. Face Tracking

34. Face Tracking (cont’d)

35. Hand Gesture Recognition
 Smart Human-Computer User Interfaces
 Sign Language Recognition

36. Human Activity Recognition

37. Medical Applications
 skin cancer breast cancer

38. Morphing

39. Inserting Artificial Objects into a Scene

40. Companies In this Field In India and came
to IITK*
 Sarnoff Corporation
 Kritikal Solutions
 National Instruments
 GE Laboratories
 Ittiam, Bangalore
 Interra Systems, Noida
 Yahoo India (Multimedia Searching)
 nVidia Graphics, Pune (have high requirements)
 ADE Bangalore, DRDO

41. Links for Self Study and a little Play
 http://undergraduate.csse.uwa.edu.au/units/2
33.412/
 http://www.netnam.vn/unescocourse/compute
rvision/computer.htm
 Book: Digital Image Processing, 2nd Edition
by Gonzalez and Woods, Prentice Hall

42. Good Luck !!!