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Lecturer(s)
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Kaiser Zbyněk, Ing. Ph.D.
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Polák Zdeněk, Ing. Ph.D.
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Steidl Roman, Ing. Ph.D.
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Course content
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1. Optics, lenses - properties (focal length, aperture), lens distortion and aberration. Light sensors, crop factor, depth of field, white balance. 2. Llight sensors - human eye, CCD, CMOS , CMOS and special light sensors. Colour scanning, principles of auto-focusing and image stabilisation. 3.-4. Fundamental image processing methods (image acquisition, image pre-processing, segmentation, shape description and object recognition). 5. Machine vision - fundamentals, framegrabbers, vision systems,smart cameras, objective lenses. 6. Machine vision - cameras - kinds of cameras, interface, colour formats, parameters and function. 7. Machine vision - lighting systems.
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Learning activities and teaching methods
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Lecture supplemented with a discussion, Laboratory work
- Team project (50/number of students)
- 25 hours per semester
- Contact hours
- 39 hours per semester
- Presentation preparation (report) (1-10)
- 10 hours per semester
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| prerequisite |
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| Competences |
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| N/A |
| N/A |
| N/A |
| N/A |
| learning outcomes |
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| Knowledge |
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| to explain basic physical principles of optics |
| to describe the lens parameters and distortions |
| to explain the principles of capturing monochrome and colour images |
| to explain basic methods of image processing |
| to describe components of machine vision systems |
| Skills |
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| to analyze a general machine vision task |
| to design a machine vision system |
| to apply basic image processing methods |
| Competences |
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| N/A |
| N/A |
| teaching methods |
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| Knowledge |
|---|
| Lecture supplemented with a discussion |
| Laboratory work |
| Self-study of literature |
| Skills |
|---|
| Laboratory work |
| Project-based instruction |
| Competences |
|---|
| Lecture supplemented with a discussion |
| Laboratory work |
| Project-based instruction |
| assessment methods |
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| Knowledge |
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| Oral exam |
| Written exam |
| Project |
| Skills |
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| Project |
| Group presentation at a seminar |
| Competences |
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| Oral exam |
| Written exam |
| Project |
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Recommended literature
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Gonzales, Rafael C.; Woods, Richard E. Digital image processing. 2nd ed. Upper Saddle River : Prentice Hall, 2002. ISBN 0-201-18075-8.
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Hlaváč, Václav; Sedláček, Miloš. Zpracování signálů a obrazů. Dotisk 2. vyd. Praha : Vydavatelství ČVUT, 2005. ISBN 80-01-03110-1.
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Kotek, Zdeněk, Mařík, Vladimír. Metody rozpoznávání a jejich aplikace. Academia, Praha, 1993. ISBN 80-200-0297-9.
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Sonka, Milan; Boyle, Roger; Hlavac, Vaclav. Image processing, analysis, and machine vision. 2nd ed. Pacific Grove : PWS Publishing, 1999. ISBN 0-534-95393-X.
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Šonka, Milan; Hlaváč, Václav. Počítačové vidění. Praha : Grada, 1992. ISBN 80-85424-67-3.
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