StudiesCourses
Image Processing II

Image Processing II: Algorithms and Applications

The solution of an image processing task usually consists of several interrelated steps, such as preprocessing, object segmentation and feature extraction, with the aim of reliably detecting characteristic properties of a test object. In the case of an automatic test or classification, these features can be used to obtain information about the object condition or the type of object. For this purpose, among other things, algorithms for pattern recognition, methods for three-dimensional object reconstruction (e.g. stereo vision, triangulation methods) and the fundamentals of machine learning are developed and applied. In this course, various methods and algorithms for the IT analysis of pixel data up to a statement about the quality of a test object are presented and the interaction of the sub-steps is illustrated using practical examples.

COURSE REGISTRATION AND MATERIALS

Further information on this module can be found in the online course catalog and in Stud.IP. In addition, you have to register your participation in this event in Stud.IP.

Lecture and exercise documents etc. can be found under the respective event in Stud.IP.


Your Lecturer in this Module

Dr.-Ing. Bettina Altmann
Former Members of Staff
Dr.-Ing. Bettina Altmann
Former Members of Staff

Your Tutor

Hagen Bossemeyer, M. Sc.
Research Staff
Address
An der Universität 1
30823 Garbsen
Building
Room
129
Hagen Bossemeyer, M. Sc.
Research Staff
Address
An der Universität 1
30823 Garbsen
Building
Room
129