Basics of Digital Image Processing

546 views

Published on

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

Published in: Education
  • Nice !! Download 100 % Free Ebooks, PPts, Study Notes, Novels, etc @ https://www.ThesisScientist.com
       Reply 
    Are you sure you want to  Yes  No
    Your message goes here
  • Be the first to like this

Basics of Digital Image Processing

  1. 1. The Electronics Club
  2. 2. INTRODUCTION TO DIGITAL IMAGE PROCESSING
  3. 3. What is DIP? What are the related fields? How are they related? Why are they studied together? Tools Required? Applications’ Demos! AGENDA
  4. 4. COMPUTER VISION ACQUIRE PROCESS ANALYZE UNDERSTAND Images or high dimensional data to produce numerical i.e. create mathematical models by optimizing the problem.
  5. 5. 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.
  6. 6. SIGNAL PROCESSING Deals with operations on or analysis of analog as well as digitized signals, representing time- varying or spatially varying physical quantities.
  7. 7. 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"
  8. 8. NEURAL NETWORKS Input Neurons- Image Input Next level Neurons- For transformation and Output Neurons- Gives the output Applications: Handwriting recognition
  9. 9. 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.
  10. 10. 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
  11. 11. MATHEMATICS • Fourier Transform • Eigen Vectors and Eigen Values • Calculus • Vectors and Spaces • Probability and Statistics • Linear Algebra
  12. 12. Image Enhancement
  13. 13. Image Enhancement
  14. 14. Image Enhancement
  15. 15. Image Enhancement
  16. 16. Image Restoration
  17. 17. Image Compression
  18. 18. Image Segmentation
  19. 19. Image Segmentation
  20. 20. Image Inpainting
  21. 21. Image Inpainting
  22. 22. Image Inpainting
  23. 23. IMAGES
  24. 24. RGB
  25. 25. GRAY SCALE
  26. 26. BINARY
  27. 27. CODE SNIPPET
  28. 28. Edge Detection
  29. 29. CODE SNIPPET
  30. 30. GAUSSIAN NOISE
  31. 31. SPECKLE NOISE
  32. 32. POISSON NOISE
  33. 33. De-noising
  34. 34. CODE SNIPPET
  35. 35. CODE SNIPPET
  36. 36. THANK YOU

×