PA173 Mathematical Morphology

Faculty of Informatics
Spring 2009
Extent and Intensity
2/1. 3 credit(s) (plus extra credits for completion). Type of Completion: zk (examination).
doc. RNDr. Petr Matula, Ph.D. (lecturer)
Guaranteed by
prof. Ing. Jiří Sochor, CSc.
Department of Visual Computing - Faculty of Informatics
Contact Person: doc. RNDr. Petr Matula, Ph.D.
Mon 11:00–11:50 B311, Mon 12:00–13:50 C416
Knowledge at the level of course PV131 Digital Image Processing is useful.
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
there are 18 fields of study the course is directly associated with, display
Course objectives
The lecture is focused on mathematical morphology in image analysis. The methods will be discussed from theoretical, application and algorithmic point of view. Students can try the methods on simple practical examples in class exercises.
  • Structuring element and its decomposition
  • Fundamental morphological operators (erosion, dilation, opening, closing, top-hat, ...)
  • Hit-or-miss transform, skeletons, thinning, thickening
  • Geodesic transformations and metrics
  • Morphological reconstructions
  • Morphological filters
  • Segmentation, watershed transform, markers
  • Efficient implementation of morphological operators
  • Granulometry, classification, texture analysis
  • SOILLE, Pierre. Morphological Image Analysis: Principles and Applications. 2nd edition. Berlin: Springer-Verlag, 2003. ISBN 3-540-42988-3. info
Assessment methods
Written as well as oral examination. Attendance at class excercises required. Study materials in English. Teaching in English or Czech (in the case of all enrolled students prefer Czech)
Language of instruction
Further Comments
The course is taught annually.
The course is also listed under the following terms Spring 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, Spring 2023.
  • Enrolment Statistics (Spring 2009, recent)
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