| Course Type | Elective Course |
|---|
| Course Level | Master's Degree With Thesis |
|---|
| Year of Study | - |
|---|
| Semester | - |
|---|
| ECTS | 10 |
|---|
| Name of Lecturer(s) |
- |
| Learning Outcomes |
At the end of this course, the students;
- Know about history and applications of image processing.
- Learn digital image processing models.
- Learn spatial and gray-level resolution.
- Learn pixel basis image operations.
- Learn and apply arithmetic/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, image formation; image model, imaging devices, low level vision: smoothing, edge detection, edge linking, multiscale approaches, Intermediate level vision: surface reconstruction, shape from shading, motion and stereo, range imaging, high level vision; model-based vision, semantic nets, generalized cylinders, Hough transform. |
|---|
| Course Contents |
| WEEK |
TOPICS |
|
1st Week |
Introduction, image formation |
|
2nd Week |
Introduction, image formation |
|
3rd Week |
Image model, image acquisition schemes |
|
4th Week |
Image model, image acquisition schemes |
|
5th Week |
Imaging devices, low level vision: smoothing, edge detection, edge linking, multiscale approaches |
|
6th Week |
Imaging devices, low level vision: smoothing, edge detection, edge linking, multiscale approaches |
|
7th Week |
Intermediate level vision: surface reconstruction, shape from shading, motion and stereo, range imaging |
|
8th Week |
Midterm Exam |
|
9th Week |
Intermediate level vision: surface reconstruction, shape from shading, motion and stereo, range imaging |
|
10th Week |
High level vision: model-based vision, semantic nets, generalized cylinders |
|
11th Week |
High level vision: model-based vision, semantic nets, generalized cylinders |
|
12th Week |
High level vision: model-based vision, semantic nets, generalized cylinders |
|
13th Week |
Hough transform |
|
14th Week |
Hough transform |
|
| Recommended or Required Reading | 1. Digital Image Processing, Rafael C. Gonzales and Richard E. Woods, Prentice Hall, 2002 |
|---|
| Planned Learning Activities and Teaching Methods |
- Lecture
- Presentation
- 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 |
3 |
3 |
| Preparation for Quiz |
0 |
0 |
0 |
| Individual or group work |
14 |
8 |
112 |
| Preparation for Final exam |
1 |
40 |
40 |
| Course hours |
14 |
3 |
42 |
| Preparation for Midterm exam |
1 |
30 |
30 |
| Laboratory (including preparation) |
0 |
0 |
0 |
| Final exam |
1 |
3 |
3 |
| Homework |
2 |
35 |
70 |
| Total Work Load | 300 |
| Total Work Load / 30 (h) | 10 |
| ECTS Credit of the Course | 10 |
|
| Language of Instruction | Turkish |
|---|
| Work Placement(s) | No |
|---|
