Course detail
Image Processing
FIT-ZPOAcad. year: 2023/2024
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
Language of instruction
Number of ECTS credits
Mode of study
Entry knowledge
Rules for evaluation and completion of the course
Aims
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.
Study aids
Prerequisites and corequisites
- recommended prerequisite
Computer Graphics
Basic literature
Recommended reading
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
Elearning
Classification of course in study plans
- Programme IT-MSC-2 Master's
branch MPV , 0 year of study, summer semester, compulsory-optional
branch MBS , 0 year of study, summer semester, elective
branch MIS , 0 year of study, summer semester, elective
branch MIN , 0 year of study, summer semester, elective
branch MGM , 1 year of study, summer semester, compulsory
branch MBI , 0 year of study, summer semester, elective
branch MSK , 0 year of study, summer semester, elective
branch MMM , 0 year of study, summer semester, elective - Programme MITAI Master's
specialization NISY , 0 year of study, summer semester, elective
specialization NSPE , 0 year of study, summer semester, elective
specialization NBIO , 0 year of study, summer semester, elective
specialization NSEN , 0 year of study, summer semester, elective
specialization NVIZ , 0 year of study, summer semester, compulsory
specialization NGRI , 0 year of study, summer semester, elective
specialization NADE , 0 year of study, summer semester, elective
specialization NISD , 0 year of study, summer semester, elective
specialization NMAT , 0 year of study, summer semester, elective
specialization NSEC , 0 year of study, summer semester, elective
specialization NISY up to 2020/21 , 0 year of study, summer semester, elective
specialization NCPS , 0 year of study, summer semester, elective
specialization NHPC , 0 year of study, summer semester, elective
specialization NNET , 0 year of study, summer semester, elective
specialization NMAL , 0 year of study, summer semester, elective
specialization NVER , 0 year of study, summer semester, elective
specialization NIDE , 0 year of study, summer semester, elective
specialization NEMB , 0 year of study, summer semester, elective
specialization NEMB up to 2021/22 , 0 year of study, summer semester, elective
Type of course unit
Lecture
Teacher / Lecturer
Syllabus
- 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
Project
Teacher / Lecturer
Syllabus
- Individually assigned project for the whole duration of the course.
Elearning