1. Digital Image Processing Lecture 1: Introduction Naveed Ejaz

3. Introduction  Instructor: Naveed Ejaz  Prerequisite: None  TAs: Will be announced soon  Yahoo Group: FASTDIP2010

4. Introduction  Room N111-A  E-mail: naveed.ejaz@nu.edu.pknaveed.ejaz@nu.edu.pk

5. Text Book(s)  Gonzalez, R. C. and Woods, R. E., Digital Image Processing, Second Edition, Pearson-Prentice Hall, I nc., 2002. ISBN 81-7758-168-6.  Gonzalez, R. C., Woods, R. E., and Eddins, S. L., Digital Image Processing Using MATLAB ®, Pearson- Prentice Hall, Inc., 2004, ISBN 81-7758-898-2.

6. Grading Quizzes 10 Assignments 15 Project 10 Mid-Terms 25 Final Exam 40

7. Academic Honesty  All parties involved in any kind of cheating in any exam will get zero in that exam  Habitual cheaters will get zero in all assignments/ projects. This may lead to a course failure  Cheating punishment may become more strict

8. Guidelines  Read your email and messages on the course yahoo group regularly  Start working on projects/assignments from first day.  Come prepared in the class  Read book (s)  Remain attentive during the class

9. 9 One picture is worth more than ten thousand words

10. What is an Image?  An image may be defined as a two dimensional function f(x,y) where x and y a re spatial coordinates and amplitude of f at any pair of coordinates (x,y) is called the intensity or Graylevel of the image at that point.

11. Digital Image  When x,y and the amplitude values of f are all finite, discrete quantities, we call the imag e a Digital Image.  A digital Image is composed of a finite num ber of elements each of which has a particu lar location and value  These elements are referred to as Picture El ements, Image Elements, Pels or Pixels

12. Digital Image

13. Digital Image Processing  The DIP field refers to processing Digital Images by means of Digital Computer

14. Related Areas  Image Analysis  Computer Vision ( Emulating Human Vision ) A clear distinction between these three Areas is not there

15. Classification of DIP and Computer Vision Processes

16. 16 Image Processing Steps

17. Why do we Process Images?

19. Applications of Image Processing

20. 1. Image Restoration

21. Image Colorization

22. Image Enhancement

23. Extraction of Satellite Area from an Aerial Image

24. Face Detection

25. Face Tracking

26. Face Morphing

27. Finger Print Recognition

28. Application: Medical Imaging Scan DataModel Fitting Prototype Kidney Model Resulting Kidney and spinal cord instance

29. 29 Image Processing Examples Magnetic Resonance Imaging (MRI) is useful for scanning tissues

30. 30 Image Processing Examples Edge Extraction

31. 31 Image Processing Examples Segmentation

32. 32 Image Processing Examples Extraction of Settlement Area from and Arial image

33. 33 Image Processing Examples Face Detection Image shows the ground displacement of a typical area due to e arthquake

34. 34 Image Processing Examples Face Tracking Image shows the ground displacement of a typical area due to e arthquake

35. 35 Image Processing Examples Fingerprint Recognition Faulty Image of Saturn Recovered Image

36. 6/23/2016 36 Brain Inspector Brain Tumor Detection and 3D Visualization: The Process Scanning MRI Images through MRI Machine Brain MRI Scans in DICOM Format Brain MRI Scans in bmp Format Brain Image Segmentatio n & Comparison 2D Tumor Detection 3D Brain Modeling 3D tumor visualization Semantic Decision Suppo rt

37. 6/23/2016 37 Brain Inspector 3D Visualization of Brain Tumor

38. 38 DIP Related Projects Remote Surgery Adult Filtration Watermarking Visible Invisible Gender Classification Facial Expression Classification Video Processing Segmentation Watermarking Object Tracking Driver Fatigue Detection