PB130dist Introduction to Digital Image Processing

Faculty of Informatics
Spring 2026
Extent and Intensity
2/0/0. 2 credit(s) (plus extra credits for completion). Type of Completion: zk (examination).
Asynchronous teaching
Teacher(s)
doc. RNDr. Petr Matula, Ph.D. (lecturer)
Guaranteed by
doc. RNDr. Petr Matula, Ph.D.
Department of Visual Computing – Faculty of Informatics
Supplier department: Department of Visual Computing – Faculty of Informatics
Prerequisites
! ( PB130 Intro Digital Image Processing || NOW( PB130 Intro Digital Image Processing ))
Knowledge of high-school mathematics and understanding and design of simple algorithms is supposed.
Course Enrolment Limitations
The course is offered to students of any study field.
The capacity limit for the course is 150 student(s).
Current registration and enrolment status: enrolled: 3/150, only registered: 0/150, only registered with preference (fields directly associated with the programme): 0/150
Abstract
The objective of this course is to introduce students to digital image processing and provide the necessary background for further study in the field, especially within the N-VIZ and N-VIZ_A study programmes. This course is an online, English-language alternative to the PB130 course and is intended for self-study without traditional lectures or programming seminars. It is primarily designed for students entering Master’s study programmes from other universities.
Learning outcomes
At the end of the course a student should: know the basic terminology related to digital image processing; know about the typical problems from digital image processing; understand the principle of simple algorithms for image processing and know how to use them. The course is intended as an introduction to digital image processing.
Key topics
  • Image acquisition and basic image computer representations. 
  • Histograms and Noise. 
  • Point transformations. 
  • Convolution and linear filters. 
  • Differential filters and edge detection. 
  • Non-linear filters. 
  • Basics of digital geometry. 
  • Mathematical morphology. 
  • Image segmentation and basics of neural networks
  • Object and image description.
  • Color images. 
Study resources and literature
    required literature
  • BURGER, Wilhelm and Mark James BURGE. Digital image processing : an algorithmic introduction using Java. 1st ed. New York: Springer, 2008, xx, 564. ISBN 9781846283796. info
    recommended literature
  • ŠONKA, Milan; Václav HLAVÁČ and Roger BOYLE. Image processing analysis and machine vision. 2nd ed. Pacific Grove: PWS Publishing, 1999, xxiv, 770. ISBN 053495393X. info
    not specified
  • GONZALEZ, Rafael C. and Richard E. WOODS. Digital image processing. 3rd ed. Upper Saddle River, N.J.: Pearson Prentice Hall, 2008, xxii, 954. ISBN 9780135052679. info
Approaches, practices, and methods used in teaching
The students will obtain on-line access to the study materials of PB130 course in English. While there will be no regular lectures, individual consultations about the course content are possible.
Method of verifying learning outcomes and course completion requirements
Written final exam with an oral part if needed, no materials allowed.
Language of instruction
English
Study support
http://is.muni.cz/auth/el/fi/jaro2026/PB130dist/index.qwarp
Further comments (probably available only in Czech)
Study Materials
The course is taught each semester.
Listed among pre-requisites of other courses
Teacher's information
It is expected that the students will follow the interactive syllabus or the course in the information system and at the end of the semester write a final exam.
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