[ INMAWKVDBVA ] KV Digital Image Processing

Workload Education level Study areas Responsible person Hours per week Coordinating university
3 ECTS M1 - Master's programme 1. year Computer Science Josef Scharinger 2 hpw Johannes Kepler University Linz
Detailed information
Original study plan Master's programme Computer Science 2022W
Objectives Students understand the principles of processing, analysis, compression and protection of digital images.
Subject Concept and generation of digital images, discrete transforms for digital images, restoration of images, geometric operations on digital images, digital image enhancement,segmentation of images, feature extraction from images, classification of objects in images, image recognition using convolutional neural networks (CNNs), object detection and segmentation using R-CNNs, semantic segmentation using FCNs, JPEG-standards for image compression, digital watermarking.

Project: students have to choose, analyze, and document (in groups) a practical digital image processing system.

Criteria for evaluation Written exam at the end of the semester; realization, presentation and documentation of (small) practical project.
Methods Slide presentation with case studies on the blackboard; project
Language German
Study material PDF-versions of the slides used in the lecture will be made available via KUSSS.

Recommended reading:

  • Klaus D. Tönnies (2005). Grundlagender Bildverarbeitung. Person Studium.
Changing subject? No
Further information
On-site course
Maximum number of participants -
Assignment procedure Direct assignment