|
|
Main menu for Browse IS/STAG
Course info
KEI / EPZ
:
Course description
Department/Unit / Abbreviation
|
KEI
/
EPZ
|
Academic Year
|
2023/2024
|
Academic Year
|
2023/2024
|
Title
|
Image Processing Systems
|
Form of course completion
|
Pre-Exam Credit
|
Form of course completion
|
Pre-Exam Credit
|
Accredited / Credits
|
Yes,
3
Cred.
|
Type of completion
|
Combined
|
Type of completion
|
Combined
|
Time requirements
|
Lecture
1
[Hours/Week]
Tutorial
2
[Hours/Week]
|
Course credit prior to examination
|
No
|
Course credit prior to examination
|
No
|
Automatic acceptance of credit before examination
|
Yes in the case of a previous evaluation 4 nebo nic.
|
Included in study average
|
NO
|
Language of instruction
|
Czech, English
|
Occ/max
|
|
|
|
Automatic acceptance of credit before examination
|
Yes in the case of a previous evaluation 4 nebo nic.
|
Summer semester
|
0 / -
|
0 / -
|
0 / -
|
Included in study average
|
NO
|
Winter semester
|
7 / -
|
0 / -
|
0 / -
|
Repeated registration
|
NO
|
Repeated registration
|
NO
|
Timetable
|
Yes
|
Semester taught
|
Winter semester
|
Semester taught
|
Winter semester
|
Minimum (B + C) students
|
8
|
Optional course |
Yes
|
Optional course
|
Yes
|
Language of instruction
|
Czech, English
|
Internship duration
|
0
|
No. of hours of on-premise lessons |
|
Evaluation scale |
S|N |
Periodicity |
každý rok
|
Periodicita upřesnění |
|
Fundamental theoretical course |
No
|
Fundamental course |
No
|
Fundamental theoretical course |
No
|
Evaluation scale |
S|N |
Substituted course
|
None
|
Preclusive courses
|
N/A
|
Prerequisite courses
|
N/A
|
Informally recommended courses
|
N/A
|
Courses depending on this Course
|
N/A
|
Histogram of students' grades over the years:
Graphic PNG
,
XLS
|
Course objectives:
|
The objective of this course is to acquaint students with basic principles of image processing from image acquisition to pattern recognition. The course presents machine vision systems and their design and applications in more details.
|
Requirements on student
|
A necessary condition for credits is participation in labs and presentation of a project in NI Vision Builder.
|
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.
|
Activities
|
|
Fields of study
|
|
Guarantors and lecturers
|
-
Guarantors:
Ing. Radek Holota, Ph.D. (100%),
-
Lecturer:
Ing. Jaroslav Fiřt, Ph.D. (30%),
Ing. Radek Holota, Ph.D. (70%),
-
Tutorial lecturer:
Ing. Petr Burian, Ph.D. (100%),
Ing. Jaroslav Fiřt, Ph.D. (40%),
Ing. Radek Holota, Ph.D. (60%),
|
Literature
|
-
Basic:
Gonzales, Rafael C.; Woods, Richard E. Digital image processing. 2nd ed. Upper Saddle River : Prentice Hall, 2002. ISBN 0-201-18075-8.
-
Basic:
Kotek, Zdeněk, Mařík, Vladimír. Metody rozpoznávání a jejich aplikace. Academia, Praha, 1993. ISBN 80-200-0297-9.
-
Basic:
Šonka, Milan; Hlaváč, Václav. Počítačové vidění. Praha : Grada, 1992. ISBN 80-85424-67-3.
-
Basic:
Hlaváč, Václav; Sedláček, Miloš. Zpracování signálů a obrazů. Dotisk 2. vyd. Praha : Vydavatelství ČVUT, 2005. ISBN 80-01-03110-1.
-
Extending:
Sonka, Milan; Boyle, Roger; Hlavac, Vaclav. Image processing, analysis, and machine vision. 2nd ed. Pacific Grove : PWS Publishing, 1999. ISBN 0-534-95393-X.
-
On-line library catalogues
|
Time requirements
|
All forms of study
|
Activities
|
Time requirements for activity [h]
|
Team project (50/number of students)
|
25
|
Presentation preparation (report) (1-10)
|
10
|
Contact hours
|
39
|
Total
|
74
|
|
Prerequisites
|
Competences - students are expected to possess the following competences before the course commences to finish it successfully: |
N/A |
N/A |
N/A |
N/A |
|
Learning outcomes
|
Knowledge - knowledge resulting from the course: |
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 - skills resulting from the course: |
to analyze a general machine vision task |
to design a machine vision system |
to apply basic image processing methods |
Competences - competences resulting from the course: |
N/A |
N/A |
|
Assessment methods
|
Knowledge - knowledge achieved by taking this course are verified by the following means: |
Oral exam |
Written exam |
Project |
Skills - skills achieved by taking this course are verified by the following means: |
Project |
Group presentation at a seminar |
Competences - competence achieved by taking this course are verified by the following means: |
Oral exam |
Written exam |
Project |
|
Teaching methods
|
Knowledge - the following training methods are used to achieve the required knowledge: |
Lecture supplemented with a discussion |
Laboratory work |
Self-study of literature |
Skills - the following training methods are used to achieve the required skills: |
Laboratory work |
Project-based instruction |
Competences - the following training methods are used to achieve the required competences: |
Lecture supplemented with a discussion |
Laboratory work |
Project-based instruction |
|
|
|
|