Title:

Image Processing

Code:ZPO
Ac.Year:2018/2019
Sem:Summer
Curriculums:
ProgrammeFieldYearDuty
IT-MSC-2MBI-Elective
IT-MSC-2MBS-Elective
IT-MSC-2MGM1stCompulsory
IT-MSC-2MGMe1stCompulsory
IT-MSC-2MIN-Elective
IT-MSC-2MIS-Elective
IT-MSC-2MMI1stCompulsory
IT-MSC-2MMM-Elective
IT-MSC-2MPV-Compulsory-Elective - group M
IT-MSC-2MSK-Elective
Language of Instruction:Czech
News:Vážení studenti,

vítejte v předmětu. Prosím, pokud by něco z vysvětlení bylo nesrozumitelné nebo kdybyste měli připomínky nebo kolize, dejte nám, prosím, vědět.

Pavel Zemčík, Víťa Beran


Poznámka: Je otevřena i anglická verze předmětu, ZPOe, můžete tedy chodit i na přednášky v angličtině.
Credits:5
Completion:examination (written)
Type of
instruction:
Hour/semLecturesSeminar
Exercises
Laboratory
Exercises
Computer
Exercises
Other
Hours:2600026
 ExamsTestsExercisesLaboratoriesOther
Points:51100039
Guarantor:Zemčík Pavel, prof. Dr. Ing. (DCGM)
Lecturer:Bařina David, Ing., Ph.D. (DCGM)
Beran Vítězslav, Ing., Ph.D. (DCGM)
Nosko Svetozár, Ing. (DCGM)
Španěl 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: 
Computer Graphics (PGR), DCGM
Follow-ups:
Computer Vision (POVa), DCGM
Schedule:
DayLessonWeekRoomStartEndLect.Gr.Groups
FriObhajoby projektů2019-05-03G202 09:0011:50
FrilecturelecturesE105 12:0013:501MIT 2MIT MGM MMI xx
FriPrezentace projektů2019-04-05E104 14:0016:50
FriObhajoby projektů2019-05-03E104 14:0016:50
 
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:
 
  1. Introduction, representation of image, linear filtration  (8. 2. 2019 Zemčík slides, slides, demo)
  2. Image acquisition (15. 2. 2019 Zemčík? slides)
  3. Discrete image transforms, FFT, relationship with filtering(Zemčík 22. 2. 2019 slajdy a slides)
  4. Point image transforms (1. 3. 2019 Beran slajdy, demo.zip)
  5. Edge detection, segmentation (8. 3. 2019 Beran slides, examples)
  6. Resampling, warping, morphing (15. 3. 2019 Zemčík slides)
  7. DCT, Wavelets (22. 3. 2019 Bařina slides)
  8. Watermarks (29. 3. 2019 Beran/Zemčík? slides)
  9. Test + project status presentation (5. 4. 2019 Beran)
  10. Image distortion, types of noise, optimal filtration (12. 4. 2019 Španěl slides)
  11. no lecture - Good Friday (19. 4. 2019)
  12. Project defences + misc. (26. 4. 2019 Beran)
  13. Matematical morphology, motion analysis, conclusion (3.5. Španěl slides)
Syllabus - others, projects and individual work of students:
 
  1. Individually assigned project for the whole duration of the course.
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
Study literature:
 
  • Russ, J.C.: The Image Processing Handbook, CRC Press 1995, ISBM 0-8493-2516-1
Progress assessment:
  Mid-term test, individual project.
 

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