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Image segmentation is a fundamental task of image processing that consists in partitioning the image by grouping pixels into homogeneous regions. We propose a novel segmentation algorithm that consists in combining many runs of a simple and fast randomized segmentation algorithm. Our algorithm also yields a soft-edge closed contour detector. We describe the theoretical probabilistic framework and report on our implementation that experimentally corroborates that performance increases with the number of runs.