Course details


Computer Vision

L + P
WS 2020 Prof. Dr.-Ing. Gunther Heidemann, Ulf Krumnack, Axel Schaffland
B.Sc modules:
CS-BWP-INF - Informatics
CS-BWP-NI - Neuroinformatics
KOGW-WPM-INF - Computer Science
KOGW-WPM-NI - Neuroinformatics
M.Sc modules:
CC-MWP-NI - Neuroinformatics
CS-MWP-NI - Neuroinformatics
KOGW-MWPM-NIR - Major subject Neuroinformatics and Robotics

Master elective course
Tue: 14-16
Wed: 10-12
Thu: 10-12

Both the rapid growth of image and video data and new applications such as robotics require automated image processing. This course introduces the basic concepts of artificial vision. Topics: Image acquisition and representation; mathematical background; basic point operations; linear and nonlinear filtering; morphological pattern recognition; color (perceptual aspects and technical representation); gray-, color- and texture-segmentation; image reconstruction and enhancement; object recognition; compression; applications (e.g., image search in databases). A focus is on object recognition, where topics range from simple edge based methods and template matching over traditional approaches like PCA over Boosting, SIFT and SURF to (deep) neural networks.