Subject
Digital image processing
| 1. | Course Title |
Digital image processing Digital image processing |
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| 2. | Code | F18L2S095 | ||||||||||||
| 3. | Study Programme | — | ||||||||||||
| 4. | Organizer of the study programme (unit, institute, department or division) | Faculty of Computer Science and Engineering | ||||||||||||
| 5. | Degree level (first, second, third cycle) | First Cycle | ||||||||||||
| 6. | Academic year / semester | 4 / Summer | ||||||||||||
| 7. | Number of ECTS credits | 6 | ||||||||||||
| 8. | Teacher | — | ||||||||||||
| 9. | Prerequisites for enrolling in the course | Discrete Mathematics or Discrete Structures 2 | ||||||||||||
| 10. | Objectives of the course programme (competences) | Upon completion of the course, the student is expected to master and use the basic tools and methods for image processing. | ||||||||||||
| 11. | Course content | Historical overview; Types of images and image creation devices; Image display; Digital images and pixels; Color components; Overview of applications and examples of digital image processing; Image digitization: 2-D sampling and reconstruction; quantization; digitization; Introduction to OpenCV and Python; Basic image operations; Pixel-level transformations in images; Image histogram; Image contrast and gamma; Histogram equalization; Adaptive histogram equalization; Color space; Linear filters and convolution; Image smoothing and sharpening; Edge detection: gradient-based methods, Laplacian-based methods; edge merging; Image segmentation: threshold-based segmentation; region-based segmentation; Morphological operations on an image: dilation/erosion; opening/closing; boundary extraction; region filling; connected component extraction; thinning; thickening; skeletonization; 2-D Fourier transform and properties. Wavelets and multiresolution processing. Image templates and pyramids; Image compression; Shape detection in images and contour analysis; Extraction of visual features from images. Keypoint detection; Panoramic images; Application of image processing algorithms. | ||||||||||||
| 12. | Learning methods | Lectures supported by slide presentations, interactive lectures, exercises (using equipment and software packages), teamwork, case studies, guest lecturers, independent preparation and defense of a project assignment and seminar paper, learning in an electronic environment (forums, consultations). | ||||||||||||
| 13. | Total available time | 6 ECTS x 30 hours = 180 hours | ||||||||||||
| 14. | Distribution of available time | 30 + 45 + 15 + 15 + 75 = 180 hours | ||||||||||||
| 15. | Forms of teaching activities |
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| 16. | Other forms of activities |
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| 17. | Assessment method |
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| 18. | Grading criteria (points / grade) |
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| 19. | Requirement for obtaining a signature and taking the final exam | completed activities 15.1 and 15.2 | ||||||||||||
| 20. | Language of instruction | Macedonian and English | ||||||||||||
| 21. | Method for monitoring the quality of teaching | internal evaluation and survey mechanism | ||||||||||||
| 22. | Literature |
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