Course details
Image Processing (in English)
ZPOe Acad. year 2024/2025 Summer semester 5 credits
Introduction to image processing, image acquiring, point and discrete image transforms, linear image filtering, image distortions, types of noise, optimal image filtering, non-linear image filtering, watermarks, edge detection, segmentation, motion analysis, loseless and lossy image compression
Guarantor
Course coordinator
Language of instruction
Completion
Time span
- 26 hrs lectures
- 26 hrs projects
Assessment points
- 51 pts final exam
- 10 pts mid-term test
- 39 pts projects
Department
Lecturer
Beran Vítězslav, doc. Ing., Ph.D. (DCGM)
Nosko Svetozár, Ing., Ph.D. (DCGM)
Španěl Michal, doc. Ing., Ph.D. (DCGM)
Zemčík Pavel, prof. Dr. Ing., dr. h. c. (DCGM)
Instructor
Learning objectives
To get acquainted with the image processing basics theory (transformations, filtration, noise reduction, etc.). To learn how to apply such knowledge on real examples of image processing tasks. To get acquainted with "higher" imaging algorithms. To learn kow to practically program image processing applications through projects.
The students will get acquainted with the image processing basics theory (transformations, filtration, noise reduction, etc.). They will learn how to apply such knowledge on real examples of image processing tasks. They will also get acquainted with "higher" imaging algorithms. Finally, they will learn how to practically program image processing applications through projects.
Students will improve their teamwork skills and in exploitation of "C" language.
Recommended prerequisites
- Computer Graphics (PGR)
Prerequisite knowledge and skills
Programming language C, basic knowledge of computer graphics, mathematical
analysis and linear algebra.
Study literature
- Russ, J.C.: The Image Processing Handbook, CRC Press 1995, ISBM 0-8493-2516-1
- Bradski, G., Kaehler, A.: Learning OpenCV: Computer Vision with the OpenCV Library, OReilly 2008, ISBN: 978-0596516130
- Jahne, B.: Handbook of Computer Vision and Applications, Academic Press, 1999, ISBN 0-12-379770-5
- IEEE Multimedia, IEEE, USA - series of journals- various articles
Syllabus of lectures
- Image acquisition
- Applications and image representation
- Linear filtering
- Discrete image transforms, FFT, relationship with filtering
- Image distortion and optimal filtration
- Point image transforms
- Mathematical morphology (+ test and project presentations)
- Edge detection, segmentation
- DCT, Wavelets
- Resampling, warping, morphing
- Watermarks
- Project consultations or invited lecture
- Motion analysis
Syllabus - others, projects and individual work of students
Individually assigned project for the whole duration of the course.
Progress assessment
- Mid-term exam - 10 points.
- Individual project - 39 points.
- Final exam - 51 points.
Schedule
Day | Type | Weeks | Room | Start | End | Capacity | Lect.grp | Groups | Info |
---|---|---|---|---|---|---|---|---|---|
Thu | lecture | 2., 3., 4., 10., 11. of lectures | A113 | 14:00 | 15:50 | 64 | 1EIT 2EIT INTE | xx | Zemčík |
Thu | lecture | 6., 7., 8. of lectures | A113 | 14:00 | 15:50 | 64 | 1EIT 2EIT INTE | xx | Beran |
Thu | lecture | 2025-02-13 | A113 | 14:00 | 15:50 | 64 | 1EIT 2EIT INTE | xx | Nosko |
Thu | lecture | 2025-03-13 | A113 | 14:00 | 15:50 | 64 | 1EIT 2EIT INTE | xx | Španěl |
Thu | lecture | 2025-04-10 | A113 | 14:00 | 15:50 | 64 | 1EIT 2EIT INTE | xx | Bařina |
Course inclusion in study plans
- Programme MIT-EN (in English), any year of study, Compulsory-Elective group B