Title:

Image Processing

Code:ZPO
Ac.Year:2005/2006
Term:Summer
Curriculums:
ProgrammeFieldYearDuty
IT-BC-3BIT-Elective
IT-MSC-2MGM.1stCompulsory
IT-MSC-2MIN.1stElective
IT-MSC-2MIS.-Elective
IT-MSC-2MPS-Elective
Language of Instruction:Czech
Credits:5
Completion:examination (written)
Type of
instruction:
Hour/semLecturesSem. ExercisesLab. exercisesComp. exercisesOther
Hours:2600026
 ExaminationTestsExercisesLaboratoriesOther
Points:50100040
Guarantor:Honec Jozef, doc. Ing., CSc., DAME
Lecturer:Potúček Igor, Ing., Ph.D., DCGM
Španěl Michal, Ing., Ph.D., DCGM
Zemčík Pavel, prof. Dr. Ing., DCGM
Instructor:Beran Vítězslav, Ing., Ph.D., DCGM
Faculty:Faculty of Electrical Engineering and Communication BUT
Department:Department of Control and Instrumentation FEEC BUT
Prerequisites: 
Computer Graphics (PGR), DCGM
Follow-ups:
Computer Vision (POV), DCGM
 
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 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, the will learn kow to practically program image processing applications through projects.
Generic learning outcomes and competences:
  Students will improve their teamwork skills and in exploitation of "C" language.
Syllabus of lectures:
 
  1. Introduction to image processing
  2. Image data acquiring, image defects
  3. Point image transforms, colors
  4. 2D Fourier transform
  5. Linear image filtering
  6. Fourier transform and Fourier domain properties
  7. Discrete cosine transform and others, applications
  8. Geometrical image transforms
  9. Image morphology and nonlinear image filtering
  10. Image edge detection and object detection
  11. Image distortion, types of noise and optimal filtering
  12. Watermarks
  13. Future of image processing
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
  • Forsyth, D. A., Ponce, J.: Computer Vision: A Modern Approach, Prentice Hall, 2003. ISBN 0-13-191193-7
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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