| Course Unit Title | Course Unit Code | Type of Course Unit | Level of Course Unit | Year of Study | Semester | ECTS Credits |
|---|---|---|---|---|---|---|
| Image Processing | TBL426 | Elective | Bachelor's degree | 4 | Fall | 5 |
Name of Lecturer(s)
Associate Prof. Dr. Süleyman EKEN
Associate Prof. Dr. Özkan KAFADAR
Associate Prof. Dr. Serdar SOLAK
Learning Outcomes of the Course Unit
1) You can define the properties of the image and kind.
2) It may explain the sampling of the image signal.
3) Image formats, able to distinguish the image enhancement techniques.
4) Image filtering and sort of explain.
5) Two-dimensional Fourier transform of the image and can explain the fast fourier.
Program Competencies-Learning Outcomes Relation
| Program Competencies | ||||||||||||
| 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | ||
| Learning Outcomes | ||||||||||||
| 1 | No relation | High | No relation | No relation | No relation | High | High | No relation | High | No relation | No relation | |
| 2 | No relation | High | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | |
| 3 | High | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | |
| 4 | High | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | |
| 5 | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | |
Mode of Delivery
Face to Face
Prerequisites and Co-Requisites
None
Recommended Optional Programme Components
Not Required
Course Contents
1. Fundamentals of image, properties of light, color information, the human visual system, cameras, computer vision systems, black-and-white image, a color image, color model (RGB, CMY, TIQ), digital image 2. sampling of the image signal and quantified 3 image formats, image enhancement techniques; point processing, black-and-white image, slicing the value of gray, adjust brightness, contrast enhancement and computer applications 4. Image filter systems 5. Two-dimensional image transformations; applied to two-dimensional Fourier transform and fast Fourier transformation images 6. The image data coding techniques, image compression and techniques
Weekly Schedule
1) Introduction to image processing and basic consept2) Computer software used for image processing (Matlab, OPENCV)
3) Color spaces used in image processing (RGB, HSV, HSI, CMY)
4) Filters used in image processing (low pass and high pass filter)
5) Binary and grey image applications
6) Image Enhancement and Segmentation Operations
7) Fourier Transformations and Image Processing Applications
8) 1-dimensional and 2-dimensional signal processing, Image processing in frequency domain, mathematical basis of Fast Fourier Transform
9) Midterm exam
10) Morphological operations
11) Moment operation
12) Stereo vision and applications
13) Project evaluation
14) Project evaluation
15) Project evaluation
16) Final exam
Recommended or Required Reading
1- An Introduction to Digital Image Processing with Matlab
2- Learning OpenCV
3- Digital Image Processing, Rafael C. Gonzalez, Richard E. Woods
Planned Learning Activities and Teaching Methods
1) Lecture
2) Question-Answer
3) Discussion
4) Drill and Practice
5) Self Study
6) Problem Solving
Assessment Methods and Criteria
Contribution of Project to Course Grade |
60% |
|---|---|
Contribution of Final Examination to Course Grade |
40% |
Total |
100% |
Language of Instruction
Turkish
Work Placement(s)
Not Required