PV131 Digital Image Processing

Faculty of Informatics
Autumn 2002
Extent and Intensity
2/1. 3 credit(s) (plus extra credits for completion). Recommended Type of Completion: zk (examination). Other types of completion: k (colloquium), z (credit).
prof. RNDr. Michal Kozubek, Ph.D. (lecturer)
Mgr. Jiří Stibor (seminar tutor)
doc. RNDr. David Svoboda, Ph.D. (seminar tutor)
Guaranteed by
prof. RNDr. Luděk Matyska, CSc.
High-Resolution Cytometry Laboratory - Department of Machine Learning and Data Processing - Faculty of Informatics
Contact Person: prof. RNDr. Michal Kozubek, Ph.D.
Tue 8:00–9:50 D2
  • Timetable of Seminar Groups:
PV131/01: each odd Monday 11:00–12:50 B311, D. Svoboda
PV131/02: each even Monday 11:00–12:50 B311, D. Svoboda
PV131/03: each odd Friday 14:00–15:50 B311, J. Stibor
PV131/04: each even Friday 14:00–15:50 B311, J. Stibor
! P131 Digital Image Processing
Knowledge at the level of the following courses is assumed: M000 Mathematical Analysis I, M003 Linear Algebra I, V001 English exam.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
Course objectives
The aim of this lecture is to introduce the students to the basics of digital image processing. The students will gain knowledge about the available techniques and possibilities of this field. The lecture serves as the base for all those who want to attend to the topic in more details.
  • Acquisition of 2D and 3D image data, process of signal digitization.
  • Properties of the digital image, types of noise.
  • Fourier transform and Nyquist sampling theorem.
  • Convolution, PSF, OTF.
  • Image preprocessing, linear and non-linear filters.
  • Deconvolution.
  • Edge detection.
  • Global and local thresholding, binary image and its modification.
  • Mathematical morphology.
  • Image segmentation.
  • Object description.
  • Object classification.
  • Digital image processing in practice, biomedical applications.
  • PRATT, William K. Digital image processing. 2nd ed. New York: John Wiley & Sons, 1991. xiv, 698. ISBN 0471857661. info
  • SONKA, Milan, Václav HLAVÁČ and Roger BOYLE. Image processing analysis and machine vision [2nd ed.]. 2nd ed. Pacific Grove: PWS Publishing, 1999. xxiv, 770. ISBN 0-534-95393-X. info
  • ŠONKA, Milan and Václav HLAVÁČ. Počítačové vidění. Praha: Grada, 1992. 252 s. ISBN 80-85424-67-3. info
Language of instruction
Follow-Up Courses
Further Comments
The course is taught annually.
Listed among pre-requisites of other courses
Teacher's information
The course is also listed under the following terms Autumn 2003, Autumn 2004, Autumn 2005, Autumn 2006, Autumn 2007, Autumn 2008, Autumn 2009, Autumn 2010, Autumn 2011, Autumn 2012, Autumn 2013, Autumn 2014, Autumn 2015, Autumn 2016, Autumn 2017, Autumn 2018, Spring 2020, Spring 2021, Spring 2022.
  • Enrolment Statistics (Autumn 2002, recent)
  • Permalink: https://is.muni.cz/course/fi/autumn2002/PV131