# FI:PA173 Mathematical Morphology - Course Information

## PA173 Mathematical Morphology

**Faculty of Informatics**

Spring 2024

**Extent and Intensity**- 2/2/0. 3 credit(s) (plus extra credits for completion). Recommended Type of Completion: zk (examination). Other types of completion: z (credit).

Taught in person. **Teacher(s)**- doc. RNDr. Petr Matula, Ph.D. (lecturer)
**Guaranteed by**- doc. RNDr. Petr Matula, Ph.D.

Department of Visual Computing – Faculty of Informatics

Contact Person: doc. RNDr. Petr Matula, Ph.D.

Supplier department: Department of Visual Computing – Faculty of Informatics **Timetable**- Thu 10:00–11:50 B411
- Timetable of Seminar Groups:

*P. Matula* **Prerequisites**- Knowledge at the level of course PB130 Introduction to 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.

The capacity limit for the course is 24 student(s).

Current registration and enrolment status: enrolled:**9**/24, only registered:**0**/24, only registered with preference (fields directly associated with the programme):**0**/24 **fields of study / plans the course is directly associated with**- there are 53 fields of study the course is directly associated with, display
**Course objectives**- The objective of the course is to introduce mathematical morphology theory, algorithms, and applications to students interested in digital image processing.
**Learning outcomes**- At the end of the course students should be able to: understand and explain the principles of mathematical morphology methods and efficient algorithms for their computation; respect their properties and theoretical limits; demonstrate their usage on typical image analysis problems in various application fields; solve image analysis problems using mathematical morphology.
**Syllabus**- 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, hierarchical segmentation
- Efficient implementation of morphological operators
- Granulometry, classification, texture analysis

**Literature**- SOILLE, Pierre.
*Morphological Image Analysis: Principles and Applications*. 2nd edition. Berlin: Springer-Verlag, 2003. ISBN 3-540-42988-3. info

*recommended literature*- SOILLE, Pierre.
**Teaching methods**- Lectures followed by class exercises in a computer room to gain hands-on experience.
**Assessment methods**- Attendance at class exercises required, written as well as oral examination. In the written part, 55 points can be obtained by presenting correct results of morphological transforms on given 1D functions, and 45 points in typically eight open-style questions. To continue to the oral part, the students must achieve at least 50 points from the written part. The oral part is a discussion about the written part testing understanding the main concepts.
**Language of instruction**- English
**Further Comments**- Study Materials

The course is taught annually.

- Enrolment Statistics (recent)

- Permalink: https://is.muni.cz/course/fi/spring2024/PA173