1. IMAGE PROCESSING >Introduction Digital images & histograms
UTRECHT UNIVERSITY
Deb Panja
Ronald Poppe

2. TODAY
Course info Image processing Histograms

3. Course info

4. Course overview Your lecturers:
Ronald Poppe – last 8 lectures (coordinator)
Deb Panja – first 7 lectures
Practicum assistants:
Casper Hagenaars
Daphne Odekerken
Ruben Schenkhuizen
Exercise assistant:
Federico D’Ambrosio

5. Course overview2
Website: (link on cs education page)
Course form:
Lectures (15)
Exercise sessions (2)
Mid-term and final exam
Assignments (3)
Walk-in sessions for assignments (5)

6. Course overview3 After the course, you should possess knowledge on:
Introduction to basic manipulations of images
From acquisition to complex processing
Insights into image processing concepts
(these will be tested using the exams)
And you should also develop skills on:
Experience in using and developing a variety of image processing techniques
(these will be tested by assignments)

7. Course overview4 Course material
Principles of Digital Image Processing" by Burger & Burge:
Book 1: Fundamental Techniques
Book 2: Core Algorithms
Book 3: Advanced Methods
Download from SpingerLink (free if you access through the UU)
Advanced Engineering Mathematics (10th Edition)" by Erwin Kreyszig
Only Chapter 11.2 and 11.9 (will be provided by us)

8. Course overview5
Lecture 1: Digital images and histograms Lecture 2: Point operators Lecture 3: Filters Lecture 4: Edges Lecture 5: Spectral techniques (Fourier transform) Lecture 6: Discrete Fourier transform Lecture 7: Fourier shape descriptor and Q&A Lecture 8: Color spaces and quantization Lecture 9: Filters and edge detection for color images Lecture 10: Morphological filters Lecture 11: Regions in binary images Lecture 12: Detecting simple curves and corners Lecture 13: Automatic thresholding Lecture 14: Comparing images Lecture 15: Recap and Q&A

9. Course overview6 Slides are part of the course material
Will be available on the course website
Exercise (and assignment) sessions are good preparation for exams
Covers topics not included in assignments
We encourage active participation so don’t hold back with questions and remarks

10. Course overview7
The assignment is to gain hands-on expertise with image processing tasks:
Assignment 1: Filters and edges (deadline September 24, 23:00)
Assignment 2: Morphological filters (deadline October 18, 23:00)
Assignment 3: Shape detection (deadline November 12, 23:00)
Assignments are mandatory
Carried out in pairs (so find one)
C# framework available
Assignments are essential part of the course, so start early!
No re-take!

11. Course overview8
Assignments are increasingly difficult, and require increasing levels of creativity
Grading per assignment is provided
Grade 8 if you finish the basic tasks perfectly, 2 points bonus for additional work
Plan ahead:
Final exam and final assignment deadline are in the same week
Student assistants can help with the assignment in the walk-in sessions (5)
Register on Slack ( for Q&A

12. Course overview9
Regarding deadlines, there are very few excuses when you find out:
There is not enough time
The software framework doesn’t work
In the last week that your partner didn’t do anything
So start early and notify us as soon as possible when things go wrong

13. Course overview10
Exam:
Mid-term (covers lectures 1-7): Friday October 6 (11:00 – 12:45)
Final (covers lectures 1-15): Friday November 10 (8:30 – 10:30)
Do not expect us to simply repeat questions from previous years or from the exercises (we expect you to be think, analyze and be creative)
There will be an exam Q&A in the last lecture before each exam
We will provide example questions during the Q&A sessions
You can submit questions that we will elaborate on during these lectures

14. Course overview11 The grading is as follows:
Final is 50% assignments ( )%, 50% exams (20+30)%
Conditions:
Weighted average of exams should be at least grade 4
Weighted average of assignments should be at least grade 4
No mid-term retake
No show in an exam means you get zero for that exam
Retake decision will be taken based on your final grade before the retake
Final grade should be at least 5.5

15. Course overview12 Contact:
ONLY us about extending deadlines when you have a VERY good reason
DO us if you don’t partner for the assignment
DO us if your partner does not put in the effort (don’t wait too long)
Help:
Questions during/before/after lectures
Exercise/walk-in sessions
Feedback via Slack
Feedback via mail

16. Course overview13 Your responsibilities (and our expectations):
Register for the course (ASAP)
Find a partner for the assignments (ASAP)
Register on Slack (
Master the topics on the course (lectures, exercises, slides)
Develop insight and practical experience through assignments (mandatory)
Pass the exams (mandatory)
Don’t underestimate:
The difficulty of some of the topics in the course (especially maths)
The time it takes to finish the assignments
The lack of time in the final weeks of the block

17. Course overview14 Our responsibilities:
Compact-concise-connected set of topics
Thought-through exercises and assignments
Make the material “as simple as possible, but not simpler”
Provide help when needed

18. Course overview15 In summary:
You will gain relevant knowledge, insights and expertise
You will have a solid base in image processing, and might consider the course “Computer Vision” when doing a master
This is a very interesting and fun course!
You will have to spend some time though
Don’t underestimate the maths

19. Questions?

20. Next lecture

21. Next lecture Next lecture is about:
Point operators (Book I, Chapter 4)
Wednesday September 9, 15: :00 (RUPPERT-042)
Deadline for Assignment 1 (Filters and edges):
September 24, 23:00
Walk-in September 22, 9:00-10:45
Find a partner!

22. Contents of this lecture

23. Contents of this lecture
Fundamental techniques (book I)
Chapter 1: Digital images
Chapter 3: Histograms