PA166 Advanced Methods of Digital Image Processing

Faculty of Informatics
Spring 2005
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)
doc. RNDr. Pavel Matula, Ph.D. (lecturer)
doc. RNDr. Petr Matula, Ph.D. (lecturer)
Guaranteed by
prof. PhDr. Karel Pala, CSc.
High-Resolution Cytometry Laboratory – Department of Machine Learning and Data Processing – Faculty of Informatics
Contact Person: prof. RNDr. Michal Kozubek, Ph.D.
Timetable
Thu 10:00–11:50 B204
  • Timetable of Seminar Groups:
PA166/01: Fri 10:00–10:50 B311, P. Matula
PA166/02: Fri 11:00–11:50 B311, P. Matula
Prerequisites
PV131 Digital Image Processing
Knowledge at the level of the lecture PV131 is assumed.
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 7 fields of study the course is directly associated with, display
Course objectives
This course is a continuation of the course PV131. The course concerns volumetric image processing, particularly advanced mathematical morphology methods and deformable models for 3D boundary extraction. Students can try the methods on practicals.
Syllabus
  • Specifics of 3D image processing
  • Basic morphological operators (erosion, dilation, opening, closing, ...)
  • Hit-or-miss transformation, skeletons
  • Geodesic transformations and metrics
  • Morphological filtering
  • Watershed transformation, markers
  • Image registration
  • Point-set registration, ICP algorithm
  • Object reconstruction
  • Parametric, implicit and discrete deformable models
Literature
  • SOILLE, Pierre. Morphological image analysis : principles and applications. Berlin: Springer, 1999, xii, 316. ISBN 3540656715. info
  • SINGH, Ajit, Dmitry GOLDGOF and Demetri TERZOPOULOS. Deformable models in medical image analysis. Los Alamitos: IEEE Computer Society, 1998, x, 388 s. ISBN 0-8186-8521-2. info
  • LOHMANN, Gabriele. Volumetric image analysis. Chichester: Wiley-Teubner, 1998, x, 243 s. ISBN 3-519-06447-2. info
Assessment methods (in Czech)
Písemná zkouška, nutná účast na cvičeních a domácí práce.
Language of instruction
Czech
Follow-Up Courses
Further Comments
The course is taught annually.
Teacher's information
http://www.fi.muni.cz/lom/
The course is also listed under the following terms Spring 2006, Spring 2007, Spring 2008, Spring 2009, Spring 2010, Spring 2011, Spring 2012, Spring 2013, Spring 2014, Spring 2015, Spring 2016, Spring 2017, Spring 2019, Spring 2020, Spring 2021, Spring 2022, Spring 2023, Spring 2024, Spring 2025.
  • Enrolment Statistics (Spring 2005, recent)
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