Course detail
Computer Vision
FEKT-MPC-POVAcad. year: 2024/2025
The Computer Vision course addresses methods for acquisition and digital processing of an image data. The main parts of the course are technical equipments, algorithms and methods for image processing.
Language of instruction
Number of ECTS credits
Mode of study
Guarantor
Entry knowledge
Rules for evaluation and completion of the course
The content and forms of instruction in the evaluated course are specified by a regulation issued by the lecturer responsible for the course and updated for every academic year.
Aims
An absolvent of the course is able to design and to implement algorithms and methods for processing of an image data, pattern recognition and dynamic scene analysis.
Study aids
Prerequisites and corequisites
Basic literature
Recommended reading
Hlaváč V., Šonka M.: Počítačové vidění. Grada 1992. ISBN 80-85424-67-3. (CS)
Russ J.C.: The Image Processing Handbook. CRC Press 1995. ISBN 0-8493-2516-1. (EN)
Sonka M., Hlavac V., Boyle R.: Image Processing, Analysis and Machine Vision. Thomson 2008. ISBN 978-0-495-08252-1. (EN)
Classification of course in study plans
- Programme MPC-KAM Master's 2 year of study, winter semester, compulsory-optional
Type of course unit
Lecture
Teacher / Lecturer
Syllabus
2. Basic physics concepts.
3. Optics in computer vision.
4. Electronics in computer vision.
5. Segmentation.
6. Detection of geometrical primitives.
7. Objects detection and plane measuring.
8. Objects description.
9. Classification and automatic sorting.
10. Optical character recognition.
11. Motion analysis.
12. Optical 3D measuring.
13. Traffic applications.
Laboratory exercise
Teacher / Lecturer
Syllabus
1. Spectral characteristics
2. Active triangulation
3. Thermal vision
4. Hardware image processing
5. Automatic focus
6. Defectoscopy
7. Calibration of the microscope
8. Passive triangulation
9. Description and classification
10. Motion detection in a traffic task