Target skills:
The student will gain an overview on established and modern image processing techniques. The course provides tools, methods, models and techniques for the following topics: image formation, optics, imagers, color, image segmentation, image analysis, image features, image alignment, estimation in computer vision, programming and deep learning.
 
Competences:
The student will understand basic problems in image processing and machine vision, e.g. image segmentation, feature detection, image matching or estimation problems in alignment.
He/she will know methods, algorithms and common techniques to solve the above mentioned problems. The student will be able to computationally apply the methods on
given low-level and higher-level image processing tasks in real world computer vision problems.

Computer Vision with Lab
Written exam K60+Lab
Das unbenotete Labor ist Voraussetzung für die Zulassung zur Klausur K60.

4 CP, grades 1 ... 5

Prof. Dr. Rüdebusch

Master's degree program CME, EIM and MMR

Interactive Distributed Applications

Interactive Distributed Applications Lab