Image Processing I - B445008
Title: Zpracování obrazů I
Guaranteed by: Department of Mathematics, Informatics and Cybernetics (446)
Faculty: Faculty of Chemical Engineering
Actual: from 2021
Semester: winter
Points: winter s.:5
E-Credits: winter s.:5
Examination process: winter s.:
Hours per week, examination: winter s.:2/2, C+Ex [HT]
Capacity: unlimited / unlimited (unknown)
Min. number of students: unlimited
Language: Czech
Teaching methods: full-time
Teaching methods: full-time
Level:  
For type:  
Additional information: http://uprt.vscht.cz/mudrova/zob
Note: course can be enrolled in outside the study plan
enabled for web enrollment
Guarantor: Mudrová Martina Ing. Ph.D.
Interchangeability : N445022, N445022A
Examination dates   
Annotation -
Last update: Fialová Jana (15.01.2018)
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. More information is available at http://uprt.vscht.cz/mudrova/ip
Aim of the course -
Last update: Fialová Jana (15.01.2018)

Students will be able to:

save image data correctly and use colour models properly with regards to the following image data processing

handle basic tasks in image analysis

aply basic segmentation methods

use methods of frequency analysis for noise rejection and image reconstruction

assess possibilities of image processing with a goal of desired information extraction

Literature -
Last update: Fialová Jana (15.01.2018)

R: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

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

Learning resources -
Last update: Fialová Jana (15.01.2018)

http://uprt.vscht.cz/mudrova/ip

Requirements to the exam -
Last update: Fialová Jana (15.01.2018)

The subject is closed by examination and credits.

It is necessary to actively take part in lessons and seminars

Level of student assesment depends on oral presentation and two inidividual projects solved during term.

Syllabus -
Last update: Fialová Jana (15.01.2018)

1. Basic principles of raster image representation

2. Colour models, palettes, colour reduction, dithering, halftonnig

3. Histogram and its processing, contrast, brightness, gamma correction

4. Alpha blending, binary images use

5. Most important graphic formats - survey, methods of image compression

6. Geometric image transformations, interpolation in image

7. Image registration, warping, morphing

8. Methods of image acquisition and connected problems

9. Functional image transformations and their use

10. Methods of image filtering, noise rejection

11. Edge detection and its applications

12. Methods o f image sharpening

13. Mathematical morphology

14. Discussion about individual projects

Registration requirements -
Last update: Fialová Jana (15.01.2018)

Computer Science

Course completion requirements -
Last update: Mudrová Martina Ing. Ph.D. (14.02.2018)

The subject is closed by examination and credits.

It is necessary to actively take part in lessons and seminars

Level of student assesment depends on oral presentation and two inidividual projects solved during term.

Teaching methods
Activity Credits Hours
Konzultace s vyučujícími 0.2 6
Účast na přednáškách 1 28
Příprava na přednášky, semináře, laboratoře, exkurzi nebo praxi 0.5 14
Práce na individuálním projektu 1 28
Příprava na zkoušku a její absolvování 1.3 35
Účast na seminářích 1 28
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