Course detail

Image Analysis in Material Science

FSI-WONAcad. year: 2018/2019

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.

Learning outcomes of the course unit

Basic knowledge of present image processing and its use in practice.


Course of MI, MII


Not applicable.

Recommended optional programme components

Not applicable.

Recommended or required reading

Druckmüller, M., Heriban, P.: Digital Image Processing System for Windows, ver. 5.0., SOFO Brno, 1996
Hlaváč, V., Šonka, M.: Počítačové vidění, Grada, 1993

Planned learning activities and teaching methods

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

Language of instruction


Work placements

Not applicable.


The aim of the course is to provide students with information about current computer image processing methods for technical purposes.

Specification of controlled education, way of implementation and compensation for absences

Missed lessons can be compensated for via make-up topics of exercises.

Classification of course in study plans

  • Programme B3A-P Bachelor's

    branch B-MTI , 1. year of study, winter semester, 5 credits, compulsory

Type of course unit



39 hours, optionally

Teacher / Lecturer


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


14 hours, optionally

Teacher / Lecturer


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

12 hours, compulsory

Teacher / Lecturer


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.