SubjectsSubjects(version: 908)
Course, academic year 2022/2023
Advanced Image Processing - M445010
Title: Pokročilé zpracování obrazů
Guaranteed by: Department of Computing and Control Engineering (445)
Actual: from 2019
Semester: summer
Points: summer s.:4
E-Credits: summer s.:4
Examination process: summer s.:
Hours per week, examination: summer s.:1/2, C+Ex [HT]
Capacity: unknown / unknown (unknown)
Min. number of students: unlimited
Language: Czech
Teaching methods: full-time
For type: Master's (post-Bachelor)
Additional information:
Note: course can be enrolled in outside the study plan
enabled for web enrollment
Guarantor: Mudrová Martina Ing. Ph.D.
Procházka Aleš prof. Ing. CSc.
Interchangeability : N445060
Annotation -
Last update: Pátková Vlasta (20.04.2018)
Lessons and laboratory works are devoted to basic principles of acquisition, storage and processing of image digital data. There are emphasized methods which can be used in engineering image data processing in addition to general techniques. Lessons represent and operate with terms like 2D Discrete Function, Sampling, Compression, Colour Processing, Image adjustment, Image Analysis in the Image and Frequency Area, Reconstruction, Geometric Transformations, Image Registration, Objects Detection, Segmentation and Classification. Methods of discrete mathematics, statistics, Fourier transform, mathematical morphology and others constitute basic tools of image processing. Practical projects are solved in the Matlab system including its Image Processing Toolbox.
Aim of the course -
Last update: Pátková Vlasta (20.04.2018)

Students will be able to:

• aply selected advanced methods in image segmentation, registration and reconstruction

• assess critically possibilities of image processing methods application

• aply and interpret advanced methods of frequency image analysis

Literature -
Last update: Pátková Vlasta (20.04.2018)

R:Gonzales R.,Woods R.,Digital Image Processing,Prentice Hall,New Jersey,2008,9780135052679

A:Barrett H., Myers K., Foundations of Image Science,Wiley,New Jersey,2004,0471153001

A:Burger W.,Burge M., Digital Image Processing,Springer,Hagengerg,2008,9781846283796

Learning resources -
Last update: Pátková Vlasta (20.04.2018)

Requirements to the exam -
Last update: Pátková Vlasta (20.04.2018)

Credits are conditioned by activity during lessons and seminars

Level of student assessment depends on

1. Six small practical group projetcs

2. One individual project including its presentation,

3. Oral part of examination

Nothing of these three parts can be ommited.

Syllabus -
Last update: Pátková Vlasta (20.04.2018)

1. FT and its application

2. Image Reconstruction

3. Principal Component Analysis

4. Object Detection

5. Advanced Methods in Colour Reduction

6. Independent Component Analysis

7. Noise Reduction

8. 2D Interpolation

9. Image Registration

10. 2D Wavelet Tarnsform

11. Texture Classification

12. Grayscale Mathematical Morphology

13. Image Segmentation

14. Conclusion

Course completion requirements - Czech
Last update: Mareš Jan doc. Ing. Ph.D. (26.04.2018)

Vypracování a obhajoba pěti protokolů ze samostatných prací: 0 - 25 bodů

Ústní zkouška: 0-75 bodů

Celkové bodové hodnocení: 100-90 A, 89-80 B, 79-70 C, 69-60 D, 59-50 E, méně než 50 F.

Teaching methods
Activity Credits Hours
Účast na přednáškách 0,5 14
Práce na individuálním projektu 1,5 42
Příprava na zkoušku a její absolvování 1 28
Účast na seminářích 1 28
4 / 4 112 / 112