This is an introductory course for practical digital image processing using OpenCV.

1. Practical 1 - Digital Image
Processing
Aly Osama

3. “ I , ff “
“I think programming assignments
would be more useful and fun if
they were applications not
wireshark (wasn't that useful)”
“ Wireshark assignments were very
useful and I feel that project was
useless”
“ Image Processing
Course will be much
better than Computer
Networks”
“Regarding image
processing, We need
some projects worth
putting in CV”

4. Image Processing Course
“Best Course Eveeaaaaaaar”

5. Gibran Khalil Gibran

6. Lab Description
1. Talk about Industry or new Techniques in Image Processing (20 minutes)
2. Explain several algorithms using OpenCV ( 20 Minutes )
3. Practical Workshop ( 40 minutes )

7. https://www.youtube.com/watch?v=H4iRPytrnJo

8. Image Processing vs Computer Vision
Digital Image Processing: the
analysis and manipulation of a
digitized image, especially in
order to improve its quality.

9. Stages of Computer Vision

10. OpenCV - Enabling computer vision
● Open Source Computer Vision library
● Cross-platform
● Free for use under open source BSD
license
● Can be easily used with Java, Python, C
and C++
● Supports Machine Learning libraries
such as TensorFlow and Caffe.
● https://opencv.org

11. This Workshop
We’ll be using OpenCV with Python
New to Python? Check this video (Learn python in OneVideo)
https://www.youtube.com/watch?v=N4mEzFDjqtA

12. Part 1 - Acquisition of Image Data
1. Test Library
2. Load Image
3. Load Video

13. 1. 1 Test Library

14. 1.2 Importing Image
This code imports an image and
outputs it to a window and waits for
any user keyboard input to
terminate.

15. cv2.imread()

17. cv2.imshow()

18. cv2.waitKey()

19. 1.3 Importing Video

20. cv2.VideoCapture

21. Using webcam

22. Part 2 : Image Processing

23. Image Type and Content

24. Colored Image

25. Image Kernels
http://setosa.io/ev/image-kernels/

26. Blurring images in OpenCV

28. Practical Demo
Simple Object Tracking Demo

29. Useless Marks
Coursework ( Total 40 points )
● 1 Quiz (5 points)
● 3 Assignments ( 5 points * 3 ) - two weeks each -
● 1 Project ( 15 points ) - Four weeks -
● Bonus
○ 1 Quiz ( 5 points )
○ 1 Assignment ( 5 points )
○ Lab interaction ( 5 points )

30. Assignment 1
● Description: Implement any 5 filters of Instagram filters
● Points: 5 points
● Deliverables:
○ Jupyter (html) notebook
○ Input: image
○ Implement Function:
■ insta_like(image,filter_name)
○ Output: new image for each filter
● Deadline: 25th Feb. at 11:00 pm
● Hint: https://goo.gl/RDpcCn