Course detail

Computer Vision Applications

FEKT-NAPVAcad. year: 2014/2015

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

English

Number of ECTS credits

5

Mode of study

Not applicable.

Guarantor

Ing. Karel Horák, Ph.D.

Department

Department of Control and Instrumentation (UAMT)

Learning outcomes of the course unit

Graduate is 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

The knowledge on the level of the Bachelor's degree is required in the Application of Computer Vision course.

Co-requisites

Not applicable.

Planned learning activities and teaching methods

Teaching methods include lectures and practical laboratories. Course is taking advantage of e-learning (Midas) system. Students have to write a single project/assignment during the course.

Assesment methods and criteria linked to learning outcomes

Weekly laboratory exercises (24 pts), projects (16 pts) and a final exam (60 pts) are evaluated during the Application of Computer Vision course. For successful pass the course, obtaining of at least half of available points is required in all mentioned parts.

Course curriculum

1. Applications of computer vision
2. Basic physical principles
3. Hardware specifics
4. Development tools
5. Objects detection and planar measurement
6. Defectoscopy and classification
7. Optical 3D measurement
8. Object tracking
9. Optical character recognition
10. Biometry, medicine and biology
11. Traffic tasks
12. Specialized applications

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

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)

Classification of course in study plans

  • Programme EECC-MN Master's

    branch MN-KAM , 1 year of study, summer semester, elective specialised

Type of course unit

 

Lecture

26 hod., optionally

Teacher / Lecturer

Ing. Karel Horák, Ph.D.

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 hod., compulsory

Teacher / Lecturer

Ing. Karel Horák, Ph.D.

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