Course: Image Processing Systems

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Course title Image Processing Systems
Course code KEI/EPZ
Organizational form of instruction Lecture + Tutorial
Level of course Master
Year of study not specified
Semester Winter
Number of ECTS credits 3
Language of instruction Czech, English
Status of course Compulsory
Form of instruction Face-to-face
Work placements This is not an internship
Recommended optional programme components None
Lecturer(s)
  • Burian Petr, Ing. Ph.D.
  • Holota Radek, Ing. Ph.D.
  • Fiřt Jaroslav, Ing. Ph.D.
Course content
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.

Learning activities and teaching methods
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
prerequisite
Competences
N/A
N/A
N/A
N/A
learning outcomes
Knowledge
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
to analyze a general machine vision task
to design a machine vision system
to apply basic image processing methods
Competences
N/A
N/A
teaching methods
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
Knowledge
Oral exam
Written exam
Project
Skills
Project
Group presentation at a seminar
Competences
Oral exam
Written exam
Project
Recommended literature
  • Gonzales, Rafael C.; Woods, Richard E. Digital image processing. 2nd ed. Upper Saddle River : Prentice Hall, 2002. ISBN 0-201-18075-8.
  • Hlaváč, Václav; Sedláček, Miloš. Zpracování signálů a obrazů. Dotisk 2. vyd. Praha : Vydavatelství ČVUT, 2005. ISBN 80-01-03110-1.
  • Kotek, Zdeněk, Mařík, Vladimír. Metody rozpoznávání a jejich aplikace. Academia, Praha, 1993. ISBN 80-200-0297-9.
  • Sonka, Milan; Boyle, Roger; Hlavac, Vaclav. Image processing, analysis, and machine vision. 2nd ed. Pacific Grove : PWS Publishing, 1999. ISBN 0-534-95393-X.
  • Šonka, Milan; Hlaváč, Václav. Počítačové vidění. Praha : Grada, 1992. ISBN 80-85424-67-3.


Study plans that include the course
Faculty Study plan (Version) Category of Branch/Specialization Recommended year of study Recommended semester