Course details
Image Processing
ZPO Acad. year 2022/2023 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 (written part)
- 10 pts mid-term test (written part)
- 39 pts projects
Department
Lecturer
Beran Vítězslav, doc. Ing., Ph.D. (DCGM)
Španěl Michal, Ing., Ph.D. (DCGM)
Zemčík Pavel, prof. Dr. Ing., dr. h. c. (DCGM)
Instructor
Subject specific learning outcomes and competences
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.
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.
Recommended prerequisites
- Computer Graphics (PGR)
Prerequisite knowledge and skills
The C programming language and fundamentals of computer graphics.
Study literature
- Hlaváč, V., Šonka, M.: Počítačové vidění, GRADA 1992, ISBN 80-85424-67-3
- Jahne, B.: Handbook of Computer Vision and Applications, Academic Press, 1999, ISBN 0-12-379770-5
- Bradski, G., Kaehler, A.: Learning OpenCV: Computer Vision with the OpenCV Library, OReilly 2008, ISBN: 978-0596516130
Fundamental literature
- Hlaváč, V., Šonka, M.: Počítačové vidění, GRADA 1992, ISBN 80-85424-67-3
- Jahne, B.: Handbook of Computer Vision and Applications, Academic Press, 1999, ISBN 0-12-379770-5
- Russ, J.C.: The Image Processing Handbook, CRC Press 1995, ISBM 0-8493-2516-1
Syllabus of lectures
- Introduction, representation of image
- Linear filtration
- Image acquisition
- Discrete image transforms, FFT, relationship with filtering
- Point image transforms
- Edge detection, segmentation
- Resampling, warping, morphing
- DCT, Wavelets
- Watermarks
- Image distortion, types of noise
- Optimal filtration
- Mathematical Morphology
- Motion analysis, conclusion
Syllabus - others, projects and individual work of students
- Individually assigned project for the whole duration of the course.
Progress assessment
Mid-term test, project (homeworks and individual project).
Course inclusion in study plans
- Programme IT-MGR-2, field MBI, MBS, MIN, MIS, MMM, MSK, any year of study, Elective
- Programme IT-MGR-2, field MGM, 1st year of study, Compulsory
- Programme IT-MGR-2, field MPV, any year of study, Compulsory-Elective group M
- Programme MITAI, field NADE, NBIO, NCPS, NEMB, NEMB up to 2021/22, NGRI, NHPC, NIDE, NISD, NISY, NISY up to 2020/21, NMAL, NMAT, NNET, NSEC, NSEN, NSPE, NVER, any year of study, Elective
- Programme MITAI, field NVIZ, any year of study, Compulsory