| Course Type | Elective Course |
|---|
| Course Level | Bachelor's Degree |
|---|
| Year of Study | - |
|---|
| Semester | - |
|---|
| ECTS | 5 |
|---|
| Name of Lecturer(s) |
|
| Learning Outcomes |
At the end of this course, the students;
- Know the mid-level image processing techniques.
- Learn the morphological image processing algorithms.
- Know the image segmentation.
- Get an idea about the object recognition.
- Gain the ability to develop an application for a specific problem.
|
| Mode of Delivery | Face to face |
|---|
| Prerequisites | No |
|---|
| Recommended Optional Programme Components | None |
|---|
| Course Description | Review of digital image fundamentals. Intensity transformations. Spatial filtering. Filtering in frequency domain. Review of image restoration. Morphological image processing and some basic algorithms. Image segmentation. Representation and description, and introduction to object recognition. |
|---|
| Course Contents |
| WEEK |
TOPICS |
|
1st Week |
Discrete-time signals and systems. |
|
2nd Week |
Discrete-time signals and systems. |
|
3rd Week |
Discrete-time signals and systems. |
|
4th Week |
Sampling, reconstruction, and quantization. |
|
5th Week |
Sampling, reconstruction, and quantization. |
|
6th Week |
Digital image representation. |
|
7th Week |
Fundamentals of digital images. |
|
8th Week |
Image transformations. |
|
9th Week |
Image transformations. |
|
10th Week |
Image enhancement. |
|
11th Week |
Image enhancement. |
|
12th Week |
Image restoration. |
|
13th Week |
Image restoration. |
|
14th Week |
Image segmentation and description. |
|
| Recommended or Required Reading | 1) Digital Image Processing by Rafael C. Gonzalez and Richard E. Woods, 3rd edition
2) M. Sonka, V. Hlavac, R. Boyle, "Image Processing, Analysis, and Machine Vision".
3) A. K. Jain, "Fundamentals of Digital Image Processing", Prentice-Hall.
|
|---|
| Planned Learning Activities and Teaching Methods |
- Lecture
- Presentation
- Questions/Answers
- Problem Solving
- Practice
|
|---|
| Assessment Methods and Criteria |
|
Quantity |
Percentage (%) |
| Mid-term |
1 |
30 |
| Assignment |
2 |
10 |
| Quiz |
4 |
20 |
| Total(%) |
|
60 |
| Contribution of In-term Studies to Overall Grade(%) |
|
60 |
| Contribution of Final Examination to Overall Grade(%) |
|
40 |
| Total(%) |
|
100 |
|
| ECTS Allocated Based on Student Workload |
| Activities |
Quantity |
Duration (Hour) |
Total Workload (Hour) |
| Midterm exam |
1 |
2 |
2 |
| Preparation for Quiz |
0 |
0 |
0 |
| Individual or group work |
14 |
4 |
56 |
| Preparation for Final exam |
1 |
18 |
18 |
| Course hours |
14 |
4 |
56 |
| Preparation for Midterm exam |
1 |
12 |
12 |
| Laboratory (including preparation) |
0 |
0 |
0 |
| Final exam |
1 |
2 |
2 |
| Homework |
5 |
1.5 |
7.5 |
| Total Work Load | 153.5 |
| Total Work Load / 30 (h) | 5.11 |
| ECTS Credit of the Course | 5 |
|
| Language of Instruction | English |
|---|
| Work Placement(s) | No |
|---|
