Knowledge-Based Vision Systems

KVS develops analysis methods for image data on the basis of Computational Intelligence. One example is data-driven model building for the characterization of defect-free textures. KVS also researches logic-based and knowledge-based modeling of quality criteria and cognitive aspects in aesthetic evaluation. Rigid and deformable geometric structures are analyzed via registration. KVS’ research results are applied to motion analysis and tracking of objects and persons as well as to quality inspection for textured or shiny surfaces and 3D structures.


Deep Learning at the Edge

Join the event in Linz

On February 7th, SCCH and its partners from H2020 ALOHA project organize an event on the topic of Deep Learning and Embedded Systems. Take part in existing talks from researchers and professionals in this field.

Rise of AI

Conference review

Dr. Thomas Hoch participated in the RISE of AI in Berlin on May 15. At the joint stand of Upper Austrian Research GmbH and he presented the AI topics of SCCH.

New Employee at SCCH

Just in time after the Easter holidays SCCH got a new employee - even if he is not made of flesh and blood but of metal and silicon and consumes a lot of electricity.

For completing the habilitation!


Dr. Bernhard Moser finished his habilitation at the Johannes Kepler University Linz with great sucess.

Best Paper Award

At the OAGM conference

Bernhard Moser and Christian Motz won the Best Paper Award of the OAGM/AARP 2016 (Austrian Association for Pattern Recognition).

Biomedical Image Analysis

New paper online

Dr. Julian Mattes and his research partners have published a new paper with the title "Associating approximate paths and temporal sequences of noisy detections: Application to the recovery of spatio-temporal cancer cell trajectories".

No nanoparticle shall evade us!

New process developed for measuring nanoparticles

In the realm of the project “Nanoparticle Tracking”, funded by the Austrian Research Promotion Agency, researchers at Software Competence Center Hagenberg (SCCH) have succeeded in significantly improving the analysis of nanoparticle samples.

Wide-Ranging applications for Motion Analysis

Extracting information from motion patterns

Automated motion analysis is an innovative technology that extracts information from motion patterns in objects or persons and processes such information using special mathematical methods. New developments in sensor technology and greater availability of computing power enables the analysis and optimization of ever more complex motion problems in industry, sports and medicine, e.g., motion analysis of stomach cancer cells for the purpose of precise diagnosis and therapy.