DPGZO Computer Graphics and Image Processing

Faculty of Informatics
Spring 2020
Extent and Intensity
3/0/2. 5 credit(s). Type of Completion: z (credit).
Teacher(s)
prof. RNDr. Michal Kozubek, Ph.D. (lecturer)
prof. Ing. Jiří Sochor, CSc. (lecturer)
prof. RNDr. Jaroslav Koča, DrSc. (lecturer)
doc. Fotios Liarokapis, PhD (lecturer)
doc. RNDr. Pavel Matula, Ph.D. (lecturer)
doc. RNDr. Petr Matula, Ph.D. (lecturer)
doc. RNDr. Petr Sojka, Ph.D. (lecturer)
doc. RNDr. David Svoboda, Ph.D. (lecturer)
Guaranteed by
prof. RNDr. Petr Hliněný, Ph.D.
Faculty of Informatics
Supplier department: Faculty of Informatics
Prerequisites (in Czech)
!NOWANY( DEMBSY Embedded systems , DFOME Formal Methods , DMKZI Quantum Information Processing , DMPOS Computer Networks Methods , DMZDD Digital Data Processing , DPITS EIT Systems and Services , DZPJUI NLP and AI Methods , DPOSO Advances in Concurrency , DRPSEC Research in comp.security ) && SOUHLAS
Course Enrolment Limitations
The course is only offered to the students of the study fields the course is directly associated with.
fields of study / plans the course is directly associated with
Course objectives
The student will gain a deeper knowledge about a chosen field of computer graphics or image processing while working on one of the more complex projects solved in the Laboratory of Human-Computer Interactions or Laboratory of Optical Microscopy, respectively, and will apply this knowledge during the work on a team R&D project. This will strengthen the student's capability of analyzing real-world problems in the given field, finding suitable solutions and working in a scientific team.
Learning outcomes
During their doctoral studies students
- will learn to look for open research problems;
- will know select adequate research methods, theoretical and experimental;
- will practise in writing, presenting and defending their research results;
- will improve their skills working in teams;
- will improve their skills leading small research and development teams;
Syllabus
  • Computer graphics: Efficient mathematical methods and data structures for fast visualization, collision detection in real time (with object distance and intersection depth determination), filtering of position and orientation of data, interpolation and extrapolation of rotations and various specific problems. Principles together with integrated tasks are tested in three basic applications: general manipulation methods in virtual environment, visualization of binding forces between molecules and haptic visualization of 2D and 3D objects.
  • Image processing: Acquisition and evaluation of images of tissues, cells, cell nuclei, chromosomes and genes, usually for the purpose of determination of spatial arrangement of genetic material inside cell nucleus or tracking of the movement of selected cellular components in time. Especially the following methods are employed for this purpose: image filtering, image segmentation, image or object registration and object measurements on a digital grid.
Literature
  • GONZALEZ, Rafael C. and Richard E. WOODS. Digital image processing. 3rd ed. Upper Saddle River, N.J.: Pearson Prentice Hall, 2008, xxii, 954. ISBN 9780135052679. info
  • PRATT, William K. Digital image processing : PIKS scientific inside. 4th ed. Hoboken, N.J.: Wiley-interscience, 2007, xix, 782. ISBN 9780471767770. info
  • LANGETEPE, Elmar and Gabriel ZACHMANN. Geometric data structures for computer graphics. Wellesley, Mass.: A K Peters, 2006, xiii, 339. ISBN 1568812353. info
  • WATT, Alan H. 3D Computer Graphics. 3rd ed. Harlow: Addison-Wesley, 2000, xxii, 570. ISBN 0-201-39855-9. info
  • SALOMON, David. Computer graphics and geometric modeling. New York: Springer, 1999, xviii, 851. ISBN 0387986820. info
  • ŠONKA, Milan, Václav HLAVÁČ and Roger BOYLE. Image processing analysis and machine vision. 2nd ed. Pacific Grove: PWS Publishing, 1999, xxiv, 770. ISBN 053495393X. info
Teaching methods
Consultations and own research and presentation activities based on individual agreement with the supervisor. Students are engaged into the work on large R&D projects with an effort of joining international research infrastructures, such as networks of excellence or other forms of EU framework programmes. Large emphasis is put onto a team work.
Assessment methods
Communication with supervisor in Czech or English, study materials in English. Individual work, final presentation on a lab seminar. This course can be taken repeatedly.
Language of instruction
Czech
The course is also listed under the following terms Autumn 2007, Spring 2008, Autumn 2008, Spring 2009, Autumn 2009, Spring 2010, Autumn 2010, Spring 2011, Autumn 2011, Spring 2012, Autumn 2012, Spring 2013, Autumn 2013, Spring 2014, Autumn 2014, Spring 2015, Autumn 2015, Spring 2016, Autumn 2016, Spring 2017, Autumn 2017, Spring 2018, Autumn 2018, Spring 2019, Autumn 2019, Autumn 2020.
  • Enrolment Statistics (Spring 2020, recent)
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