![Image Formation
f(x,y) = reflectance(x,y) * illumination(x,y)
Reflectance in [0,1], illumination in [0,inf]](https://image.slidesharecdn.com/lecture1-150208224615-conversion-gate02/85/Lecture1-5-320.jpg)
![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
=
](https://image.slidesharecdn.com/lecture1-150208224615-conversion-gate02/85/Lecture1-8-320.jpg)
![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 ∆ apart, we can write this as:
f[i ,j] = Quantize{ f(i ∆, j ∆) }
The image can now be represented as a matrix of integer values](https://image.slidesharecdn.com/lecture1-150208224615-conversion-gate02/85/Lecture1-10-320.jpg)
Lecture1
- 1. Image Processing Lecture 1 Introduction and Application -Gaurav Gupta -Shobhit Niranjan
- 2. Instructors Gaurav Gupta Can catch at : B109/Hall-1 mail at: gauravg@iitk.ac.in gtalk: gauravg.84@GMAIL more information at: http://home.iitk.ac.in/~gauravg Shobhit Niranjan Can catch at : B211/Hall-1 mail at: nshobhit@iitk.ac.in gtalk: shobhitn@GMAIL more information at: http://home.iitk.ac.in/~nshobhit
- 3. Course Structure 1. Introduction to Image Processing, Application and Prospects (Today) 2. Introduction, Image formation, camera models and perspective geometry 3. Fourier Transform theory , Convolution and Correlation 4. Color, Image enhancement Techniques 5. Binary images: thresholding, moments, topology Note: Some topics may not be in order to maintain coherency and running time requirements. (Bare with us …trying to teach first time !!)
- 4. Today Image Formation Range Transformations Point Processing Reading for this week: Gonzalez & Woods, Ch. 3
- 5. Image Formation f(x,y) = reflectance(x,y) * illumination(x,y) Reflectance in [0,1], illumination in [0,inf]
- 8. 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 =
- 10. 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 ∆ apart, we can write this as: f[i ,j] = Quantize{ f(i ∆, j ∆) } The image can now be represented as a matrix of integer values
- 11. 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?
- 12. Negative
- 13. Log
- 16. Image Histograms
- 18. 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.
- 19. Programming Assignment #1 Easy stuff to get you started with Matlab Shobhit will hold your first tutorial Topics will be from next 2 lectures
- 23. Biometrics
- 24. Fingerprint Verification / Identification
- 25. Fingerprint Identification Research at UNR Minutiae Matching Delaunay Triangulation
- 27. Object Recognition Research reference view 1 reference view 2 novel view recognized
- 28. Indexing into Databases Shape content
- 29. Indexing into Databases (cont’d) Color, texture
- 30. Target Recognition Department of Defense (Army, Airforce, Navy)
- 31. Interpretation of aerial photography is a problem domain in both computer vision and registration. Interpretation of Aerial Photography
- 32. Autonomous Vehicles Land, Underwater, Space
- 34. Face Detection
- 35. Face Recognition
- 36. Face Detection/Recognition Research at UNR
- 38. Face Tracking
- 40. Hand Gesture Recognition Smart Human-Computer User Interfaces Sign Language Recognition
- 42. Medical Applications skin cancer breast cancer
- 43. Morphing
- 44. Inserting Artificial Objects into a Scene
- 45. 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
- 46. Links for Self Study and a little Play http://undergraduate.csse.uwa.edu.au/units/233.4 http://www.netnam.vn/unescocourse/computervis Book: Digital Image Processing, 2nd Edition by Gonzalez and Woods, Prentice Hall
- 47. Good Luck !!!