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WiSe 2016/17

Interactive Coloring Book

  • Pascal Gruppe 
  • Benjamin Mayer
  • Bastian Cornelsen

Lecture and Tutorial Media Processing

Module code inf018
Language of Instructions German
Target Group Bachelor
Stud.IP elearning.uni-oldenburg.de/dispatch.php/course/details
Area Applied Computer Science
SWS 2 + 2
ECTS 6.0

Module Contents

The lecture covers the technologies of media processing. In particular, the lecture focuses on image processing chain from digital imaging, through image pre-/and postprocessing, and image storage to image analysis. In addition to compression techniques and color space theory (RGB, HSV, YUV, CIEXYZ, ...), the topics of the lecture include image enhancement, feature extraction, feature description, image analysis and image comprehension. The lecture furthermore discusses the encoding and analysis of video and audio.

Placement in the Curriculum

The Module Human-Computer Interaction is an elective compulsory module for practical computer science. The module is offered as a lecture with an accompanying practical project of 6 ECTS (2VL + 2PR). The expected workload is 180 hours with an 56 hours of expected attendance time. The module involves independent project work in small teams. 

Learning Goals

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 COMPETENCE

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.

METHODICAL EXPERTISE

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 COMPTETENCE

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.

PERSONAL COMPETENCE

The students

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

Enrollment

Registration for the module takes place in the first semester weeks via the learning management system Stud.IP. The students will receive detailed information on attendance, tasks and dates in the first course at the beginning of the semester as well as in the learning management system Stud.IP.

Literature

[1] Wilhelm Burger und Mark James Burge. Digitale Bildverarbeitung: Eine Einführung mit Java und Image, J. Springer, 2006.

Weoqpubmascbgrterlmyno (jutta.fortmanndwy@uolmvwng.dzze) (Changed: 2020-01-23)