Course detail
Computer Vision
FEKT-MPC-POVAcad. year: 2023/2024
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
Czech
Number of ECTS credits
6
Mode of study
Not applicable.
Guarantor
Entry knowledge
The knowledge on the level of the Bachelor's degree is required in the Computer Vision course. Moreover, knowledge and skills equivalent to BZSV course are required.
Rules for evaluation and completion of the course
In the subject Computer Vision, laboratory exercises (40 points) and a final written (49 points) and oral (11 points) exam are evaluated. The written part lasts 90 minutes, no aids. The condition for admission to the exam is a credit from the exercises, ie attendance at all exercises and gaining at least 50% of points. The condition for passing the exam is to gain at least 50% of points from the final written part. Oral examination is optional.
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.
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 is able to describe algorithms for image processing and to implement them into an superordinate system of computer vision.
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.
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
Not applicable.
Prerequisites and corequisites
Not applicable.
Basic literature
Horák, K. a kol.: Počítačové vidění. Skriptum VUT v Brně. 132 s. 2008. (CS)
Recommended reading
Gonzalez R.C.,Woods R.E.: Digital Image Processing (4th Edition). Pearson 2017. ISBN 978-1292223049 (CS)
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)
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
26 hod., optionally
Teacher / Lecturer
Syllabus
1. Introduction and motivation.
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.
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
39 hod., compulsory
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
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