Course detail

Computer Vision Applications

FEKT-LAPVAcad. year: 2010/2011

Course acquaints with the most important problems of computer vision in technical practice –measuring of dimensions, position and orientation, inspection systems, OCR, 3D objects reconstruction, navigation, motion analysis etc. It introduces implementation of basic principles used in computer vision, parameters of classical and special means for image acquisition and processing. Subject matter is presented on real applications solved not only in academic (Group of computer vision UAMT) but also in commercial domain.

Language of instruction

Czech

Number of ECTS credits

5

Mode of study

Not applicable.

Learning outcomes of the course unit

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.

Prerequisites

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

Co-requisites

Not applicable.

Planned learning activities and teaching methods

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

Assesment methods and criteria linked to learning outcomes

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

Course curriculum

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

Work placements

Not applicable.

Aims

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.

Specification of controlled education, way of implementation and compensation for absences

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.

Recommended optional programme components

Not applicable.

Prerequisites and corequisites

Basic literature

Not applicable.

Recommended reading

Hlaváč V., Šonka M.: Počítačové vidění. Grada 1992. ISBN 80-85424-67-3. (CS)
Jahne B., Hausecker H., Geisler P.: Handbook of Computer Vision and Applications. Academic press 1999. ISBN 0-12-379770-5. (EN)

Classification of course in study plans

  • Programme EEKR-ML Master's

    branch ML-KAM , 1. year of study, summer semester, optional specialized

Type of course unit

 

Lecture

26 hours, optionally

Teacher / Lecturer

Syllabus

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

Laboratory exercise

26 hours, compulsory

Teacher / Lecturer

Syllabus

Individually assigned project for the whole duration of the course. Projects solved partial problems connected with research activities of Group of computer vision UAMT. Thematic domains:
- dimensions measuring
- detection and recognitions of surface defects on electronic components
- recognition of objects in image
- 3D problems
- traffic situations monitoring
- and others