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Course detail

Image Analysis in Material Science

Course unit code: FSI-WON
Academic year: 2016/2017
Type of course unit: compulsory
Level of course unit: Bachelor's (1st cycle)
Year of study: 1
Semester: winter
Number of ECTS credits:
Learning outcomes of the course unit:
Basic knowledge of present image processing and its use in practice.
Mode of delivery:
90 % face-to-face, 10 % distance learning
Prerequisites:
Course of MI, MII
Co-requisites:
Not applicable.
Recommended optional programme components:
Not applicable.
Course contents (annotation):
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.
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:
Czech
Work placements:
Not applicable.
Course curriculum:
Not applicable.
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.

Type of course unit:

Lecture: 39 hours, optionally
Teacher / Lecturer: doc. PaedDr. Dalibor Martišek, Ph.D.
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
seminars: 14 hours, compulsory
Teacher / Lecturer: doc. PaedDr. Dalibor Martišek, Ph.D.
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
seminars in computer labs: 12 hours, compulsory
Teacher / Lecturer: doc. PaedDr. Dalibor Martišek, Ph.D.
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

The study programmes with the given course