Image Analysis in Material Science (FSI-WON)

Academic year 2024/2025
Supervisor: doc. Ing. Pavel Štarha, 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.
Basic knowledge of present image processing and its use in practice.
Learning outcomes and competences:
 
Prerequisites:

Secondary school mathematics and informatics
Course contents:
 
Teaching methods and criteria:
 
Assesment methods and criteria linked to learning outcomes:
 
Controlled participation in lessons:
 
Type of course unit:
    Lecture  13 × 2 hrs. optionally                  
    Exercise  7 × 2 hrs. compulsory                  
    Computer-assisted exercise  6 × 2 hrs. compulsory                  
Course curriculum:
    Lecture

1. Image representation, basic graphics formats.
2. Colour spaces, pixel properties.
3. Basic operation with images - geometric transformations, logical operations.
4. Basics of probability and statistics.
5. Histogram and its basic meaning, brightness linear transformation.
5. Histogram and its basic meaning, linear brightness transformations.
6. Non-linear brightness transformation, histogram equalization.
7. Fourier transform and its applications.
8. Convolution, convolution theorem.
9. Linear and non-linear filters.
10. Additive noise - analysis and filtering.
11. Impulse noise - analysis and filtering.
12. Image segmentation, object analysis.
13. Moment method of object analysis.
    Exercise

Week 1: Familiarization with the tutorials.
Week 3: Basic image operations, brightness and contrast adjustment. Application of linear filters.
Week 6: Fourier spectrum of an image.
Week 7: Relationship between Fourier transform and convolution.
Week 9: Application of nonlinear filters.
Week 13: Moment method of object recognition, measurement protocol, results presentation.

Presence in the seminar is obligatory.
    Computer-assisted exercise

Week 2: Work with different graphic formats.
Week 4: Image histogram and pixel value non-linear transformation.
Week 5: Histogram equalization.
Week 10: Working with additive noise.
Week 11: Working with impulse noise.
Week 12: Thresholding, object analysis, basic statistics.

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
3. Martišek, D.: Počítačová geometrie a grafika, Brno 2017.
Literature - recommended:
1. Pratt, W. K. Digital Image Processing (Third Edition) PIKS Inside [online]. 3rd ed. New York: Wiley-Interscience, 2001 [cit. 2014-08-07]. ISBN 04-712-2132-5.
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