| Course Type | Elective Course |
| Course Level | Doctorate Of Science |
| Year of Study | - |
| Semester | - |
| ECTS | 10 |
| Name of Lecturer(s) |
|
| Learning Outcomes |
At the end of this course, the students;
- Know the history and application areas of image processing.
- Learn digital image models.
- Learn spatial and gray level solutions.
- Learns and applies arithmetic and logic operations on images.
- Learn and apply image enhancement and filtering methods.
|
| Mode of Delivery | Face to face |
| Prerequisites | No |
| Recommended Optional Programme Components | none |
| Course Description | Introduction to computer vision, image formation,Image model, image acquisition schemes,Lower-level vision problems: smoothing, edge detection, edge linking, multiscale approaches,Moderate vision problems: surface creation, drawing from tones, motion and stereo images,High-level vision problems: model-based vision, semantic networks, generalized cylinders,Hough transformation |
| Course Contents |
| WEEK |
TOPICS |
|
1st Week |
Introduction to computer vision, image formation |
|
2nd Week |
Introduction to computer vision, image formation |
|
3rd Week |
Image model, image acquisition schemes |
|
4th Week |
Image model, image acquisition schemes |
|
5th Week |
Lower-level vision problems: smoothing, edge detection, edge linking, multiscale approaches |
|
6th Week |
Lower-level vision problems: smoothing, edge detection, edge linking, multiscale approaches |
|
7th Week |
Moderate vision problems: surface creation, drawing from tones, motion and stereo images |
|
8th Week |
Midterm |
|
9th Week |
Moderate vision problems: surface creation, drawing from tones, motion and stereo images |
|
10th Week |
High-level vision problems: model-based vision, semantic networks, generalized cylinders |
|
11th Week |
High-level vision problems: model-based vision, semantic networks, generalized cylinders |
|
12th Week |
High-level vision problems: model-based vision, semantic networks, generalized cylinders |
|
13th Week |
Hough transformation |
|
14th Week |
Hough transformation |
|
| Recommended or Required Reading | Digital Image Processing, Rafael C. Gonzales and Richard E. Woods, Printice Hall, 2002. |
| Planned Learning Activities and Teaching Methods |
- Presentation
- Lecture
- Report Preparation
|
| Assessment Methods and Criteria |
|
Quantity |
Percentage (%) |
| Mid-term |
1 |
25 |
| Assignment |
1 |
25 |
| Quiz |
2 |
15 |
| Attendance |
1 |
5 |
| Total(%) |
|
70 |
| Contribution of In-term Studies to Overall Grade(%) |
|
70 |
| Contribution of Final Examination to Overall Grade(%) |
|
30 |
| Total(%) |
|
100 |
|
| ECTS Allocated Based on Student Workload |
| Activities |
Quantity |
Duration (Hour) |
Total Workload (Hour) |
| Midterm exam |
1 |
2 |
2 |
| Preparation for Quiz |
1 |
34 |
34 |
| Individual or group work |
14 |
8 |
112 |
| Preparation for Final exam |
1 |
60 |
60 |
| Course hours |
14 |
3 |
42 |
| Preparation for Midterm exam |
1 |
25 |
25 |
| Laboratory (including preparation) |
|
|
|
| Final exam |
1 |
2 |
2 |
| Homework |
2 |
10 |
20 |
| Quiz |
2 |
2 |
4 |
| Total Work Load | 301 |
| Total Work Load / 30 (h) | 10.03 |
| ECTS Credit of the Course | 10 |
|
| Language of Instruction | Turkish |
| Work Placement(s) | No |