The objective of “Image Processing” course is to teach the fundemantal technologies and algorithms for representation, compression and analysis of digital images in spatial and frequency domain. In this context the course also aims for introducing principle components of an image analysing system.
Prerequisite(s)
None
Corequisite(s)
None
Special Requisite(s)
The minimum qualifications that are expected from the students who want to attend the course.(Examples: Foreign language level, attendance, known theoretical pre-qualifications, etc.)
-“Fundamentals of Digital Image Processing”, A. K. Jain, Prentice Hall, Addison-Wesley, 1989.
Course Schedules
Week
Contents
Learning Methods
1. Week
Fundamentals of Image Processing
Theory
2. Week
Image Restoration-I
Theory, Practice
3. Week
Spatial Domain Filters
Theory, Practice
4. Week
Frequency Domain Filters
Theory, Practice
5. Week
Image Restoration-II
Theory, Practice
6. Week
Lossless Image Compression
Theory, Practice
7. Week
Lossy Image Compression
Theory, Practice
8. Week
Binary Image Processing
Theory, Practice
9. Week
Midterm Exam
Midterm Exam
10. Week
Morphological Image Processing, Color Image Processing
Theory, Practice
11. Week
Image Segmentation – I (Edge Detection)
Theory, Practice
12. Week
Image Segmentation – II (Thresholding)
Theory, Practice
13. Week
Image Representation and Description
Theory, Practice
14. Week
Object Recognition
Theory, Practice
15. Week
16. Week
17. Week
Assessments
Evaluation tools
Quantity
Weight(%)
Midterm(s)
1
40
Homework / Term Projects / Presentations
2
20
Final Exam
1
40
Program Outcomes
PO-1
Have scientific research in mathematics and computer science in the level of theoretical and practical knowledge.
PO-2
On the basis of undergraduate level qualifications, develop and deepen the same or a different areas of information at the level of expertise, and analyze and interpret by using statistical methods
PO-3
Develop new strategic approaches for the solution of complex problems encountered in applications related to the field and unforeseen and take responsibility for the solution.
PO-4
Evaluate critically skills acquired in the field of information in the level of expertise and assess the learning guides.
PO-5
Transfer current developments in the field and their work to the groups inside and outside the area supporting with quantitative and qualitative datas as written, verbal and visual by a systematic way.
PO-6
Use information and communication technologies with computer software in advanced level.
PO-7
Develop efficient algorithms by modeling problems faced in the field and solve such problems by using actual programming languages.
PO-8
Respect to social, scientific, cultural and ethical values at the stages of data collection related to the field, interpretation, and implementation.
PO-9
To solve problems related to the field, establish functional interacts by using strategic decision making processes.
PO-10
Establish and discuss in written, oral and visual communication in an advanced level by using at least one foreign language.
Learning Outcomes
LO-1
Learn different representations of digital images in computer systems.
LO-2
Understand mathematical foundations of image processing.
LO-3
Analyze essential algorithms about image processing.
LO-4
Gain fundamental knowledge for solving real life image processing problems.
