Course detail
Image Analysis in Material Science
FSI-WON Acad. year: 2022/2023 Winter semester
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.
Language of instruction
Czech
Number of ECTS credits
5
Supervisor
Department
Learning outcomes of the course unit
Basic knowledge of present image processing and its use in practice.
Prerequisites
Course of Mathematics I, Mathematics II
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
Aims
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.
The study programmes with the given course
Programme B-ZSI-P: Fundamentals of Mechanical Engineering, Bachelor's
specialization MTI: Materials Engineering, compulsory
Type of course unit
Lecture
39 hours, optionally
Teacher / Lecturer
Syllabus
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
14 hours, optionally
Syllabus
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
Syllabus
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.