FI:PV162 Image Processing Project - Course Information
PV162 Image Processing ProjectFaculty of Informatics
- Extent and Intensity
- 0/2. 2 credit(s) (plus extra credits for completion). Type of Completion: k (colloquium).
- doc. RNDr. Petr Matula, Ph.D. (lecturer)
doc. RNDr. David Svoboda, Ph.D. (seminar tutor)
doc. RNDr. Pavel Matula, Ph.D. (seminar tutor)
Dmitry Sorokin, Ph.D. (seminar tutor)
RNDr. Martin Maška, Ph.D. (seminar tutor)
prof. RNDr. Michal Kozubek, Ph.D. (seminar tutor)
Mgr. Karel Štěpka, Ph.D. (seminar tutor)
RNDr. Roman Stoklasa, Ph.D. (seminar tutor)
- Guaranteed by
- doc. RNDr. Petr Matula, Ph.D.
Department of Visual Computing - Faculty of Informatics
Supplier department: Department of Visual Computing - Faculty of Informatics
Knowledge at the level of course PV131 or at least PB130 is required
- 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 25 student(s).
Current registration and enrolment status: enrolled: 0/25, only registered: 0/25, only registered with preference (fields directly associated with the programme): 0/25
- Fields of study the course is directly associated with
- there are 37 fields of study the course is directly associated with, display
- Course objectives
- The course objective is to strengthen the student's capability of analyzing real-world problems in the field of digital image processing and finding suitable solutions.
- Extension and deeper knowledge of the topics presented in PV131 and PB130 with emphasis on solving a practical project. The projects are in principle of three types:
- Programming - implementation and testing of a given algorithm (in a chosen programming language)
- Creative - finding a suitable solution to a given problem
- Study - testing and comparison of several algorithms/implementations on a given data
- Articles published in scientific journals and conference proceedings according to the specification of project leader.
- Teaching methods
- The student selects a topic from a given list or suggests own topic from the field of digital image processing. (S)he works independently and is supervised by one of the tutors. The results of the work are presented at the end of the semester to other students and tutors.
- Assessment methods
- In order to obtain credits, it is necessary to finish the task (process data, write a fully functional computer program), give a presentation and discuss the results at a seminar.
- Language of instruction
- Follow-Up Courses
- Further Comments
- Study Materials
The course is taught annually.
The course is taught: every week.
- Teacher's information