
Project title:
Mathematical Methods in Image Processing under Uncertainty - MaMIPU
Duration: 2023–2026
Principal Investigator: Nebojša Ralević, PhD
Principal Investigator on Faculty: Marija Paunović, PhD
Projects call: Science Fund of the Republic of Serbia (https://fondzanauku.gov.rs/)
Program: PRISMA; Sub-program: Natural Sciences
Participating Scientific and Research Organizations: University of Novi Sad - Faculty of Technical Sciences, University of Novi Sad - Faculty of Technology Novi Sad, University of Belgrade - School of Electrical Engineering, University of Kragujevac - Faculty of Hotel Management and Tourism, Vrnjačka Banja, University of Belgrade - Faculty of Mining and Geology, University of Belgrade - Faculty of Agriculture
Abstract: The project “Mathematical Methods in Image Processing under Uncertainty” consists of three main parts.
The first part is related to computational and digital geometry and topology in image analysis and processing context. It discusses the following: Novel algorithms for moments computation; Detecting and drawing not self-crossing digital curves; Improvement of the performance of the existing 2D image repairing algorithm; Computation of the orthogonal hull of a 2D image; Applying persistent homology on related tasks; Studying the fixed point property (FPP) and its role and contribution in digital geometry and digital topology.
The second part of the project consists of: Examining the properties of distances (especially fuzzy metrics) constructed from initial distances using aggregation functions; Defining and constructing new classes of fuzzy shapes, appropriate fuzzy shape descriptors and associated measures, together with theoretical and empirical illustrations of the properties. All this new knowledge is used in image processing tasks, such as image compression through fixed point theory in fuzzy metric spaces.
The third part of the project consists of: Constructing hybrid models to support the decision uncertainty in image segmentation; Design and implementation of the Bee Colony Optimization (BCO) algorithm in software with hybrid model (based on learning techniques) for clustering problem; Optimizing Neural Networks on bioinformatics data. The examination and verification of the results require the usage of digital images obtained from a number of databases.
Project team members: Nebojša Ralević, PhD, Full Professor, Tatjana Došenović, PhD, Full Professor, Prof. Dr. Lidija Čomić, PhD, Full Professor, Bratislav Iričanin, PhD, Associate Professor Marija Paunović, PhD, Associate Professor, Nataša Milosavljević, PhD, Associate Professor, Ljubo Nedović, PhD, Associate Professor, Vladimir Ilić, PhD, Associate Professor, Dejan Ćebić, PhD, Associate Professor, Andreja Blesić, Đorđe Dragić
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