PV131 Digital Image Processing

Faculty of Informatics
Autumn 2003
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).
Teacher(s)
prof. RNDr. Michal Kozubek, Ph.D. (lecturer)
RNDr. Petr Krontorád (seminar tutor)
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.
Timetable
Fri 8:00–9:50 VC423
  • Timetable of Seminar Groups:
PV131/01: each odd Wednesday 7:00–9:50 B311, D. Svoboda
PV131/02: each even Wednesday 7:00–8:50 B311, D. Svoboda
PV131/03: each odd Tuesday 10:00–11:50 B311, J. Stibor
PV131/04: each even Tuesday 10:00–11:50 B311, J. Stibor
PV131/05: each odd Tuesday 8:00–9:50 B311, P. Krontorád
PV131/06: each even Tuesday 8:00–9:50 B311, P. Krontorád
Prerequisites
! P131 Digital Image Processing
Knowledge at the level of the following courses is required: VB001 English, MB005/MB101 Foundations of Mathematics, MB003/MB102 Linear Algebra and Geometry I, MB000/MB103 Calculus I. An advantage is knowledge at the level of MB001/MB104 Calculus II.
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.
Syllabus
  • 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.
Literature
  • PRATT, William K. Digital image processing. 3rd ed. New York: John Wiley & Sons, 2001. xix, 735. ISBN 0471374075. 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
Assessment methods (in Czech)
Přednášky v češtině, studijní materiály v angličtině. Povinná cvičení u počítačů se samostatnými úkoly k zápočtu. Závěrečná zkouška v písemné podobě bez pomůcek.
Language of instruction
Czech
Follow-Up Courses
Further Comments
The course is taught annually.
Listed among pre-requisites of other courses
Teacher's information
http://www.fi.muni.cz/lom/
The course is also listed under the following terms Autumn 2002, 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 2003, recent)
  • Permalink: https://is.muni.cz/course/fi/autumn2003/PV131