Institute of Information Theory and Automation

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Department of Image Processing

Publications ÚTIA: 
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The Department is involved in basic research in image processing and pictorial pattern recognition. Major application areas are biomedicine, remote sensing, astronomy, and art conservation.

Main scientific areas
  • Recognition of distorted images and patterns by invariant descriptors regardless of their actual position in the scene
  • Registration and fusion of several images of the same scene taken at different times, by different sensors and/or from different viewpoints in order to obtain information of higher quality
  • Theory of moment invariants, namely of rotation invariants, affine invariants and invariants to convolution
  • Restoration of degraded images, namely multichannel blind deconvolution, edgepreserving denoising, local contrast enhancement, and color transformations
  • Image forensics - detection of image forgeries
  • Cultural heritage applications - cooperation with art conservators in order to facilitate the conservation and material analysis work
2017-02-08 12:55

Department detail

Ing. Filip Antoš
Ing. Michal Bartoš Ph.D.
RNDr. Zuzana Bílková
RNDr. Jan Blažek Ph.D.
Mgr. Adam Dominec
Bc. Šimon Greško
Ing. Vít Hanousek
Ing. Jan Havrlant Ph.D.
Dr. Barmak Honarvar Shakibaei Asli Ph.D.
RNDr. Cyril Höschl Ph.D.
Ing. Jan Kamenický Ph.D.
Mgr. Tomáš Karella
Ing. Tomáš Kerepecký
Ing. Václav Košík
Ing. Jitka Kostková Ph.D.
RNDr. Jan Kotera Ph.D.
RNDr. Matěj Lébl
Ing. Babak Mahdian Ph.D.
Ing. Adam Novozámský Ph.D.
Ing. Stanislav Saic CSc.
Dr. Ing. Jan Schier
RNDr. Michal Šorel Ph.D.
Ing. Lubomír Soukup Ph.D.
Doc. Ing. Filip Šroubek Ph.D. DSc.
Ing. Tomáš Suk Ph.D. DSc.
Jana Švarcová
Ing. Milan Talich Ph.D.
RNDr. Aleš Zita
Doc. RNDr. Barbara Zitová Ph.D.
Duration: 2019 - 2020
Bilateral cooperation with University of Antwerp: Separating the invisible from the visible: mixture analysis of macroscopic elemental maps of valuable paintings
Duration: 2018 - 2021
PROVENANCE is an intermediary-free solution that gives greater control to users of social media and underpins the dynamics of social sharing in values of trust, openness, and fair participation. PROVENANCE will use blockchain to record multimedia content that is uploaded and registered by content creators or identified for registration by the PROVENANCE Social Network Monitor.
Duration: 2018 - 2020
Objects moving fast with respect to the camera appear blurred when observed. Surprisingly this common phenomenon has not yet been considered and analyzed by the computer vision community. It is the blur that encodes information about the object motion properties. Instead of considering blur as a nuisance, the project proposes to take it as a cue for detection and tracking of fast moving objects.
Duration: 2018 - 2021
The proposal falls into the area of computer image analysis and pattern recognition. It is focused on special type of data - multidimensional vector and tensor fields. Vector fields may describe particle velocity, optical/motion flow, image gradient, deformation/condutivity/diffusion tensors, and other phenomena.