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Detection of objects in noisy images and site percolation on square lattices

MPG-Autoren
http://pubman.mpdl.mpg.de/cone/persons/resource/persons84039

Langovoy,  M
Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Zitation

Langovoy, M.(2009). Detection of objects in noisy images and site percolation on square lattices (2009-035).


Zitierlink: http://hdl.handle.net/11858/00-001M-0000-0013-C21A-E
Zusammenfassung
We propose a novel probabilistic method for detection of objects in noisy images. The method uses results from percolation and random graph theories. We present an algorithm that allows to detect objects of unknown shapes in the presence of random noise. Our procedure substantially differs from wavelets-based algorithms. The algorithm has linear complexity and exponential accuracy and is appropriate for real-time systems. We prove results on consistency and algorithmic complexity of our procedure.