This is the presentation of first lecture in lecture series on digital image processing.Hope this is of your use Regards The Electronics Club (TEC) VIT university

1. The Electronics
Club

2. INTRODUCTION
TO
DIGITAL
IMAGE PROCESSING

3. What is DIP?
What are the related fields?
How are they related?
Why are they studied together?
Tools Required?
Applications’ Demos!
AGENDA

12. COMPUTER VISION
ACQUIRE
PROCESS
ANALYZE
UNDERSTAND
Images or high dimensional data to produce
numerical i.e. create mathematical models by
optimizing the problem.

13. IMAGE PROCESSING
Form of Signal processing for which the input is
an image and the output may either be an
image or a set of characteristics or parameters
related to the input.
Mostly two dimensional data.

14. SIGNAL PROCESSING
Deals with operations on or analysis of analog as
well as digitized signals, representing time-
varying or spatially varying physical quantities.

15. PATTERN RECOGNITION
To assign each input value to one of a given set
of classes and labels.
Example:
Determine whether a given email is "spam" or
"non-spam"

16. NEURAL NETWORKS
Input Neurons- Image Input
Next level Neurons- For transformation and
Output Neurons- Gives the output
Applications:
Handwriting recognition

17. MACHINE LEARNING
A branch of artificial intelligence which concerns
with the construction and study of systems that
can learn from data.
Representation and Generalization are the two
main properties of this field.

18. MACHINE VISION
The technology and methods used to provide
imaging-based automatic inspection and
analysis for applications such as automatic
inspection, process control, and robot
guidance in industry

19. MATHEMATICS
• Fourier Transform
• Eigen Vectors and Eigen Values
• Calculus
• Vectors and Spaces
• Probability and Statistics
• Linear Algebra

21. Image Enhancement

22. Image Enhancement

23. Image Enhancement

24. Image Enhancement

25. Image Restoration

26. Image Compression

28. Image Segmentation

29. Image Segmentation

30. Image Inpainting

31. Image Inpainting

32. Image Inpainting

33. IMAGES

34. RGB

35. GRAY SCALE

36. BINARY

37. CODE SNIPPET

38. Edge Detection

39. CODE SNIPPET

40. GAUSSIAN NOISE

41. SPECKLE NOISE

42. POISSON NOISE

43. De-noising

44. CODE SNIPPET

45. CODE SNIPPET

46. THANK YOU