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Study materials

Slides from lectures:

Newest version - here

Student version - here

Hough Transform - here
Radon Transform - here
First lecture - here
Second lecture - here

The files contain most of the slides used. This is not the complete content of the lecture, the knowledge recorded in the files is not sufficient to pass the exam!

Recommended literature

[1] Pratt W. K.: Digital Image Processing (3rd ed.), John Wiley, New York, 2001
[2] Gonzales R. C., Woods R. E., Digital Image Processing (2nd ed.), Prentice Hall, 2002
[3] Zitová B., Flusser J., Image registration methods: a survey. Image and Vision Computing, 21 (2003), 11, pp. 977-1000

Requirements

[1] Zoom account - the webcam will be on !
[2] GitHub account
[3] Gmail account for Colab recommended
[4] browser

We are going to take a step into the world of Image Processing using python. In order to do that, you should know the basics of Python. Please go through the following section before attending labs. Necessary information for completing all labs will be provided here. If you have any questions please contact novozamsky@utia.cas.cz

The exercises will be in Czech, but all materials and texts will be in English.

Python crash course

You should know

Learn Python

 

Labs start here!

At the beginning of every lab session join Zoom Meeting, where you receive a link for a GitHub classroom assignment. It contains all codes for an on/offline studying.

  1. Zoom link: https://cuni-cz.zoom.us/j/91367957348
  2. Get a link from your teacher, e.g. https://classroom.github.com/a/YspbK****
  3. Sign in to GitHub
    What is GitHub?
    New to GitHub? Create an account.
    Start using GitHub.
  4. If necessary, click on the "Authorize GitHub Classroom" button
  5. Find your name in the list (only for the first assignment)
  6. Click on "Accept the assignment"
  7. Go to colab.research.google.com
  8. Click on "Authorize Google Colab"
  9. Click on "GitHub" (or File > Open Notebook > GitHub)
  10. Type your GitHub user name (check "Include private repos")
  11. Find the desired repository and the notebook file
  12. Loading (In case of "Error", press "Retry")
  13. If necessary, click on the "Authorize with GitHub" button
  14. Edit the notebook, finish excercises
  15. Save in GitHub (File > Save a copy in GitHub)
 

Labs schedule