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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
Last update: Fialová Jana (15.01.2018)
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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. Last update: MUDROVAM (14.02.2018)
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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 Last update: Fialová Jana (15.01.2018)
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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. Last update: Fialová Jana (15.01.2018)
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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 Last update: Fialová Jana (15.01.2018)
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http://uprt.vscht.cz/mudrova/ip Last update: Fialová Jana (15.01.2018)
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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 Last update: Fialová Jana (15.01.2018)
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Computer Science Last update: Fialová Jana (15.01.2018)
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| 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 | ||
| 5 / 5 | 139 / 140 | |||
| Coursework assessment | |
| Form | Significance |
| Regular attendance | 20 |
| Report from individual projects | 40 |
| Oral examination | 40 |