Randomized algorithms for statistical image analysis and site percolation on square lattices
Statistics Theory
2013-12-02 v1 Probability
Methodology
Machine Learning
Statistics Theory
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.
Cite
@article{arxiv.1102.5014,
title = {Randomized algorithms for statistical image analysis and site percolation on square lattices},
author = {Mikhail A. Langovoy and Olaf Wittich},
journal= {arXiv preprint arXiv:1102.5014},
year = {2013}
}
Comments
Submitted for publication on December 11, 2009