Stud.IP Uni Oldenburg
University of Oldenburg
02.12.2022 11:19:44
inf018 - Media Processing (Course overview)
Department of Computing Science 6 KP
Module components Semester courses Wintersemester 2022/2023 Examination
Lecture
  • Unlimited access 2.01.018 - Medienverarbeitung Show lecturers
    • Prof. Dr. techn. Susanne Boll-Westermann
    • Dr.-Ing. Larbi Abdenebaoui
    • M. Sc. Mikolaj Wozniak
    • M. Sc. Tobias Lunte
    • M. Sc. Ani Withöft

    Tuesday: 10:15 - 11:45, weekly (from 18/10/22), V, Location: A05 1-160
    Wednesday: 10:15 - 11:45, weekly (from 19/10/22), PR, Location: JJW 2-233

Project
  • Unlimited access 2.01.018 - Medienverarbeitung Show lecturers
    • Prof. Dr. techn. Susanne Boll-Westermann
    • Dr.-Ing. Larbi Abdenebaoui
    • M. Sc. Mikolaj Wozniak
    • M. Sc. Tobias Lunte
    • M. Sc. Ani Withöft

    Tuesday: 10:15 - 11:45, weekly (from 18/10/22), V, Location: A05 1-160
    Wednesday: 10:15 - 11:45, weekly (from 19/10/22), PR, Location: JJW 2-233

Hinweise zum Modul
Reference text
Useful previus knowlodge: Solid programming skills in Java and/or C++, practical informatics. Interest in media processing
 
Prüfungszeiten
Die Vorstellung des praktischen Projektes an einem Projekttag aller Kleingruppen findet direkt im Anschluss an die Vorlesungszeit statt. Die mündliche Prüfung findet in den ersten beiden Wochen nach Ende der Vorlesungszeit statt. Etwaige Nachprüfungen finden am Ende der vorlesungsfreien Zeit statt. Der genaue Zeitplan kann den Webseiten der Abteilung sowie den Angaben im Lernmanagementsystem Stud.IP entnommen werden.
Module examination
Project and oral exam
The portfolio comprises two graded submodules:
  • Practical group project which progress has to be presented regularly during the tutorials.
  • Oral exam on the topics of the lecture.
Practical project and oral exam count 50% each to the final grade. Both practical project and oral exam must be passed individually.
Skills to be acquired in this module

The students can explain the basics of image processing and know which algorithms exist for the basic tasks in image processing and how these are applied.

The students can apply basic methods of image processing they learned in the lecture to solve simple problems.


**Professional compentence:**
The students
  • can name basic characteristics of digital media
  • can explain the most common methods for encoding and compressing images, video and audio
  • can describe basic procedures for image enhancement, feature extraction, feature description, image analysis and image comprehension
 

**Methodological competence:**
The students
  • can recognize and evaluate image properties and decide for suitable image processing methods
  • can select existing software packages for simple image processing problems, as well as use and customize them for their specific task
  • can implement simple image and media processing functions in a higher programming language (e.g., C ++)


 

**Social competence**
The students:

  • can plan, implement, and document a software project in team work
  • can present the results of their work to an audience and adequately respond to criticism and questions


**Self competence**
The students:

  • can accept and learn from mistakes made during the process of implementation