English

Not applicable.

Graduate would be able to consider possibility of camera systems implementation in given problem in practice, manage the design, realization and settings of some simpler computer vision problems.

It is required knowledge at bachelor study level. Prerequisite is graduation from course “Computer vision (POV)”.

Not applicable.

Teaching methods depend on the type of course unit as specified in the article 7 of BUT Rules for Studies and Examinations.

Practises: max 16 points.
Projects: max 24 poins.
Exam: max 60 poins.

1. Implementation of computer vision in technical practice – introduction, motivation, advantages and drawbacks, typical problems of camera systems applications, methodology of order process
2. Basic physical principles used in computer vision
3. Particularity of hardware for image acquisition and processing
4. Measuring in plain – precise measuring of dimensions, position and orientation
5. Detection of product presence and completeness, counting of objects in image, classification according to shape, colour, surface attributes etc.
6. Defectoscopy, inspection systems – detection of product surface defects, inspection of transparent materials etc.
7. OCR – licence plates, character reading, conversion of printed book to electronic
8. Measuring of 3D dimensions, volume metering, 3D digital models
9. Area navigation, robot positioning – 3D, trajectory monitoring
10. Motion – motion detection, moving objects detection, trajectory monitoring, 3D attributes of objects. Traffic problems – velocity measuring, red-light crossing vehicles detection, critical states detection
11. Biological images analysis, biometric data measuring
12. Other applications – contactless temperature metering (thermocamera), deformation metering (interferometer), astral sky image analysis
13. Computer vision together with computer graphics

Not applicable.

Aim of the course is to give information to students about typical applications of computer vision in industry. All aspects of camera systems design and implementation will be discussed in detail. Student will devise, debug and verify simple assignment of computer vision in semestral project.

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.

Not applicable.

Not applicable.

Jahne B., Hausecker H., Geisler P.: Handbook of Computer Vision and Applications. Academic press 1999. ISBN 0-12-379770-5. (EN)
Sonka M., Hlavac V., Boyle R.: Image Processing, Analysis and Machine Vision. Thomson 2008. ISBN 978-0-495-08252-1. (EN)