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Image segmentation by a contrario simulation (2008)
| Citations: | 6 - 0 self |
BibTeX
@MISC{Burrus08imagesegmentation,
author = {Nicolas Burrus and et al.},
title = {Image segmentation by a contrario simulation},
year = {2008}
}
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Abstract
Segmenting an image into homogeneous regions generally involves a decision criterion to establish whether two adjacent regions are similar. Decisions should be adaptive to get robust and accurate segmentation algorithms, avoid hazardous a priori and have a clear interpretation. We propose a decision process based on a contrario reasoning: two regions are meaningfully different if the probability of observing such a difference in pure noise is very low. Since the existing analytical methods are intractable in our case, we extend them to allow a mixed use of analytical computations and Monte-Carlo simulations. The resulting decision criterion is tested experimentally through a simple merging algorithm, which can be used as a post-filtering and validation step for existing segmentation methods.
Keyphrases
contrario simulation image segmentation decision criterion analytical computation homogeneous region accurate segmentation algorithm decision process validation step simple merging algorithm adjacent region segmentation method analytical method pure noise monte-carlo simulation clear interpretation contrario reasoning mixed use
