1. Course Title | Digital Image Processing | |||||||
2. Code | 3ФЕИТ05З013 | |||||||
3. Study program | KHIE, KTI | |||||||
4. Organizer of the study program (unit, institute, department) | Faculty of Electrical Engineering and Information Technologies | |||||||
5. Degree (first, second, third cycle) | First cycle | |||||||
6. Academic year/semester | IV/7 | 7. Number of ECTS credits | 6.00 | |||||
8. Lecturer | Dr Zoran Ivanovski | |||||||
9. Course Prerequisites | ||||||||
10. Course Goals (acquired competencies): The course will enable the students to understand the basics of digital image processing and mathematical methods and tools on which it is based, to test and examine practical implementations of various algorithms and to evaluate their advantages and disadvantages. By following the course the student will be able to solve various problems in the field of image processing by using and developing appropriate tools. |
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11. Course Syllabus: Basics of image processing. Image enhancement in spatial domain. Spatial filtering. Image enhancement in transform domain. Image restoration. Color image processing. Multiresolution image processing. Image compression. Edge detection. Morphological image processing. Image segmentation. Representation and description. Image analysis. |
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12. Learning methods: Combined teaching method: lecturing, tutorials and lab exercises, supported by presentations and visualization of concepts, active participation of students through tests, assignments and projects. |
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13. Total number of course hours | 3 + 1 + 1 + 0 | |||||||
14. Distribution of course hours | 180 | |||||||
15. Forms of teaching | 15.1. Lectures-theoretical teaching | 45 | ||||||
15.2. Exercises (laboratory, practice classes), seminars, teamwork | 30 | |||||||
16. Other course activities | 16.1. Projects, seminar papers | 30 | ||||||
16.2. Individual tasks | 0 | |||||||
16.3. Homework and self-learning | 75 | |||||||
17. Grading | 17.1. Exams | 10 | ||||||
17.2. Seminar work/project (presentation: written and oral) | 20 | |||||||
17.3. Activity and participation | 10 | |||||||
17.4. Final exam | 60 | |||||||
18. Grading criteria (points) | up to 50 points | 5 (five) (F) | ||||||
from 51 to 60 points | 6 (six) (E) | |||||||
from 61 to 70 points | 7 (seven) (D) | |||||||
from 71 to 80 points | 8 (eight) (C) | |||||||
from 81 to 90 points | 9 (nine) (B) | |||||||
from 91 to 100 points | 10 (ten) (A) | |||||||
19. Conditions for acquiring teacher’s signature and for taking final exam | Lectures and tutorials attendance and successful completion of lab exercises. | |||||||
20. Forms of assessment | During the semester, tests from laboratory exercises are provided (after the completion of each of the exercises). The student should also prepare a project assignment and submit it no later than the final exam. The final oral exam (duration 60 minutes) is taken in the planned exam sessions. The final grade includes the points from the tests from the laboratory exercises, the project task and the final oral exam | |||||||
21. Language | Macedonian and English | |||||||
22. Method of monitoring of teaching quality | Internal evaluation and surveys. | |||||||
23. Literature | ||||||||
23.1. Required Literature | ||||||||
No. | Author | Title | Publisher | Year | ||||
1 | R. C. Gonzalez and R. E. Woods | Digital Image Processing | Prentice Hall | 2008 | ||||
2 | Lj. Panovski | Image processing systems | 2002 | |||||
23.2. Additional Literature | ||||||||
No. | Author | Title | Publisher | Year | ||||
1 | A. K. Jain | Fundamentals of Digital Image Processing | Prentice Hall | 1989 |