Institute of Information Theory and Automation

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Doc. RNDr. Barbara Zitová, Ph.D.

Position: 
head of the department
Mail: 
Room: 
Fax: 
284680730
Phone: 
266052390
Research interests: 
All aspects of digital image processing and pattern recognition; particularly object recognition by invariants, degraded image recognition, geometric invariants, theory of moments, remote sensing and medical imaging applications, cultural heritage applications.
Publications ÚTIA: 

Barbara Zitová received her PhD degree in software systems from the Charles University, Prague, Czech Republic, in 2000. She is a head of Department of Image Processing at the Institute of Information Theory and Automation, Czech Academy of Sciences, Prague. She teaches courses on Digital Image Processing and Wavelets in Image Processing. She has authored/coauthored more than 70 research publications in these areas, including the monographs Moments and Moment Invariants in Pattern Recognition (Wiley, 2009) and 2D and 3D Image Analysis by Moments (Wiley, 2016). In 2010 she was awarded by the SCOPUS 1000 Award for receiving more than 1000 citations of a single paper. Barbara Zitová has many editorial and organizational activities. Among others, she has been an Associate Editor of the journal Pattern Recognition. 

Ph.D graduates: RNDr. Miroslav Beneš, PhD, 2014

                             Mgr. Jan Blažek, PhD, 2018

Curriculum vitae: here

Projects:

 

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Person detail

Duration: 2012 - 2014
The project deals with interdisciplinary research of digital image processing methods applied to analysis and conservation of artworks. The aim is development of image processing methods for multimodal data acquired during the analysis of historical artworks exploiting the knowledge of multispectral properties of dyes, used for artwork creation.
Duration: 2000 - 2002
The design of the automatic registration method for digital images of the same scene is the aim of the proposed project. The images can be deformed by radiometric and geometric degradations and taken by different sensors (multimodal data).