Randomized algorithms for statistical image analysis and site percolation on square lattices

2011/02/24 by Mikhail A. Langovoy, Olaf Wittich · 1 citation
Mathematics · #math.ST #math.PR #stat.ME #stat.ML #stat.TH

paper · pdf · doi:10.1111/stan.12010

Submitted for publication on December 11, 2009

arxiv created 2011/02/24 · arxiv updated 2013/12/02

Abstract

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. 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.

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• Unsupervised nonparametric detection of unknown objects in noisy images based on percolation theory