Image Analysis in Material Science (FSI-WON)

Academic year 2020/2021
Supervisor: doc. PaedDr. Dalibor Martišek, Ph.D.  
Supervising institute: ÚM all courses guaranted by this institute
Teaching language: Czech
Aims of the course unit:
The aim of the course is to provide students with information about current computer image processing methods for technical purposes.
Learning outcomes and competences:
Basic knowledge of present image processing and its use in practice.
Prerequisites:
Course of MI, MII
Course contents:
The aim of the course is to provide students with fundamental information about image
processing for technical purposes. The course deals with colour spaces and methods of
computer image modelling, brightness and kontrast modification, linear and non-linear image filters and its application, objects recognition and analysis.
Teaching methods and criteria:
The course is taught through lectures explaining the basic principles and theory of the Image Processing. Exercises are focused on practical topics presented in lectures.
Assesment methods and criteria linked to learning outcomes:
Submitted a semester work, written and oral exam
Controlled participation in lessons:
Missed lessons can be compensated for via make-up topics of exercises.
Type of course unit:
    Lecture  13 × 3 hrs. optionally                  
    Exercise  7 × 2 hrs. optionally                  
    Computer-assisted exercise  6 × 2 hrs. compulsory                  
Course curriculum:
    Lecture 1. Vector and raster graphic data, image representation, basic graphics formats.
2. Colour spaces, colour saturation, brightness and kontrast modification.
3. Basic operation with images
4. Histogram and its use
5. Histogram equalization
6. Fourier transformation and principles of its use.
7. Convolution, linear filters of low-pass and high-pass type
8. Basic non-linear filters and their ise
9. Adaptive filters
10. Image segmentation, basic methods of recognition of objects and their border lines
11. Moment metod of object analysis
12. Additive noise - analysis and filtration
13. Impulse noise - analysis and filtration
    Exercise 1. Colour saturation, brightness and contrast modification.
2. Addition, subtraction and linear combination of images
3. Basic operation with image histogram
4. Histogram equalization
5. Image segmentation, of recognition of objects and their ¨border lines
6. Object area, its center of gravity and others geometrical moments
    Computer-assisted exercise 1. Using of educational software (basic principles).
2. Work with different graphics formats.
3. Use of adaptive filters
4. Work with filters of low-pass and high-pass type
5. Work with non-linear filters
6. Work with additive noise
7. Work with impulse noise

Presence in the seminar is obligatory.
Literature - fundamental:
1. Druckmüller, M., Heriban, P.: Digital Image Processing System for Windows, ver. 5.0., SOFO Brno, 1996
2. Hlaváč, V., Šonka, M.: Počítačové vidění, Grada, 1993
The study programmes with the given course:
Programme Study form Branch Spec. Final classification   Course-unit credits     Obligation     Level     Year     Semester  
B-ZSI-P full-time study MTI Materials Engineering -- Cr,Ex 5 Compulsory 1 1 W