FI:PA173 Mathematical Morphology - Course Information
PA173 Mathematical Morphology
Faculty of InformaticsSpring 2009
- Extent and Intensity
- 2/1. 3 credit(s) (plus extra credits for completion). Type of Completion: zk (examination).
- Teacher(s)
- 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. - Timetable
- Mon 11:00–11:50 B311, Mon 12:00–13:50 C416
- Prerequisites
- 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.
- 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
- 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
- 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
- English
- Further Comments
- The course is taught annually.
- Enrolment Statistics (Spring 2009, recent)
- Permalink: https://is.muni.cz/course/fi/spring2009/PA173