PV162 Image Processing Project

Faculty of Informatics
Autumn 2024
Extent and Intensity
0/2/0. 2 credit(s) (plus extra credits for completion). Type of Completion: k (colloquium).
In-person direct teaching
Teacher(s)
doc. RNDr. Petr Matula, Ph.D. (assistant)
doc. RNDr. David Svoboda, Ph.D. (seminar tutor)
doc. RNDr. Pavel Matula, Ph.D. (lecturer)
doc. RNDr. Martin Maška, Ph.D. (seminar tutor)
Mgr. Karel Štěpka, Ph.D. (seminar tutor)
prof. RNDr. Michal Kozubek, Ph.D. (seminar tutor)
RNDr. Vladimír Ulman, 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
Prerequisites
SOUHLAS
Knowledge at the level of course PV291 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 20 student(s).
Current registration and enrolment status: enrolled: 3/20, only registered: 1/20, only registered with preference (fields directly associated with the programme): 1/20
fields of study / plans the course is directly associated with
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.
Learning outcomes
At the end of the course, the student will be able to better solve practical problems from the area of digital image processing.
Syllabus
  • Extension and more profound knowledge of the topics presented in PV291 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
Literature
  • 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
To obtain credits, the student must finish the task (process data, write a fully functional computer program), give a presentation and discuss the results at a seminar.
Language of instruction
Czech
Follow-Up Courses
Further Comments
Study Materials
The course is taught annually.
The course is taught: every week.
Teacher's information
https://cbia.fi.muni.cz/
The course is also listed under the following terms Autumn 2004, Autumn 2005, Autumn 2006, Autumn 2007, Autumn 2008, Autumn 2009, Autumn 2010, Autumn 2011, 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, Spring 2020, Autumn 2020, Spring 2021, Autumn 2021, Spring 2022, Autumn 2022, Spring 2023, Autumn 2023, Spring 2024, Spring 2025.
  • Enrolment Statistics (recent)
  • Permalink: https://is.muni.cz/course/fi/autumn2024/PV162