Title: | Image Processing |
---|
Code: | ZPO |
---|
Ac.Year: | 2017/2018 |
---|
Sem: | Summer |
---|
Curriculums: | |
---|
Language of Instruction: | Czech |
---|
Credits: | 5 |
---|
Completion: | examination (written) |
---|
Type of instruction: | Hour/sem | Lectures | Seminar Exercises | Laboratory Exercises | Computer Exercises | Other |
---|
Hours: | 26 | 0 | 0 | 0 | 26 |
---|
| Exams | Tests | Exercises | Laboratories | Other |
---|
Points: | 51 | 10 | 0 | 0 | 39 |
---|
|
---|
Guarantor: | Zemčík Pavel, prof. Dr. Ing. (DCGM) |
---|
Lecturer: | ©paněl Michal, Ing., Ph.D. (DCGM) Zemčík Pavel, prof. Dr. Ing. (DCGM) |
Instructor: | Beran Vítězslav, Ing., Ph.D. (DCGM) |
---|
Faculty: | Faculty of Information Technology BUT |
---|
Department: | Department of Computer Graphics and Multimedia FIT BUT |
---|
Prerequisites: | |
---|
Follow-ups: | |
---|
|
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. |
Description: |
---|
| | 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 |
Knowledge and skills required for the course: |
---|
| | The C programming language and fundamentals of computer graphics. |
Subject specific learning outcomes and competencies: |
---|
| | 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. |
Generic learning outcomes and competencies: |
---|
| | Students will improve their teamwork skills and in exploitation of "C" language. |
Syllabus of lectures: |
---|
|
- Introduction to image processing
- Image data acquiring
- Point image transforms
- Discrete image transforms
- Linear image filtering
- Image distortion, types of noise
- Optimal filtering
- Nonlinear image filtering
- Watermarks
- Edge detection, segmentation
- Movement analysis
- Image compression, lossy, looseless
- Future of image processing
|
Syllabus - others, projects and individual work of students: |
---|
|
- Individually assigned project for the whole duration of the course.
|
Fundamental literature: |
---|
|
- Hlaváč, V., ©onka, 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
|
Study literature: |
---|
|
- Russ, J.C.: The Image Processing Handbook, CRC Press 1995, ISBM 0-8493-2516-1
|
Progress assessment: |
---|
| | The monitored teaching activities include test (10 points), evaluated homeworks (10 points), with no replacement term, individual project (29 points), and final exam (51 points, 17 minimum to pass). The test does not have correction option, the final exam has two possible correction terms. |
|