Image analysis for biomedical and industrial applications
Principal Investigator: László Nyúl
The analysis of visual information is becoming indispensable in most areas in life and it essential to compress the image and video data, which affects all subsequent analysis. We aim to design image processing algorithms to extract the most informative pieces of data and quantitative information from single or multiple sources that can help to recognize, track and describe objects, and understand the scene. Such locally performed analysis may have a major role in telemedicine applications based on remote diagnosis and involving sensitive data, or in large (possibly ad-hoc) networks of IoT devices with limited resources. Based on the extracted information one can devise analysis and decision supporting systems that make processes more effective, can detect abnormalities or predict events, and support decision-making and prompt action in biomedical or industrial applications. We plan to evaluate the designed image descriptors and methods in real applications from various domains.
Péter Balázs, Péter Bodnár, György Kalmár, Péter Kardos, Zoltán Kató, Melinda Katona, Gábor Lékó, Antal Nagy, Gábor Németh, Csaba Olasz, Kálmán Palágyi, Judit Szűcs, Attila Tanács, Szabolcs Urbán, László Varga