FI:PA173 Mathematical Morphology - Course Information
PA173 Mathematical MorphologyFaculty of Informatics
- Extent and Intensity
- 2/2. 3 credit(s) (plus extra credits for completion). Recommended Type of Completion: zk (examination). Other types of completion: z (credit).
- 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.
Supplier department: Department of Visual Computing - Faculty of Informatics
- Mon 12:00–13:50 B411, Mon 14:00–15:50 B311
- 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
- Applied Informatics (programme FI, N-AP)
- Information Technology Security (programme FI, N-IN)
- Bioinformatics (programme FI, N-AP)
- Information Systems (programme FI, N-IN)
- Informatics (eng.) (programme FI, D-IN4)
- Informatics (programme FI, D-IN4)
- Parallel and Distributed Systems (programme FI, N-IN)
- Computer Graphics (programme FI, N-IN)
- Computer Networks and Communication (programme FI, N-IN)
- Computer Systems and Technologies (eng.) (programme FI, D-IN4)
- Computer Systems and Technologies (programme FI, D-IN4)
- Computer Systems (programme FI, N-IN)
- Embedded Systems (eng.) (programme FI, N-IN)
- Embedded Systems (programme FI, N-IN)
- Service Science, Management and Engineering (eng.) (programme FI, N-AP)
- Service Science, Management and Engineering (programme FI, N-AP)
- Social Informatics (programme FI, B-AP)
- Theoretical Informatics (programme FI, N-IN)
- Upper Secondary School Teacher Training in Informatics (programme FI, N-SS) (2)
- Artificial Intelligence and Natural Language Processing (programme FI, N-IN)
- Image Processing (programme FI, N-AP)
- Course objectives
- 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.
- 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
- SOILLE, Pierre. Morphological Image Analysis: Principles and Applications. 2nd edition. Berlin: Springer-Verlag, 2003. ISBN 3-540-42988-3. info
- Teaching methods
- Lectures followed by class exercises in a computer room to gain hands-on experience.
- 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
- Study Materials
The course is taught annually.