An efficient parallel algorithm for graph-based image segmentation

Automatically partitioning images into regions ('segmentation') is challenging in terms of quality and performance. We propose a Minimum Spanning Tree-based algorithm with a novel graph-cutting heuristic, the usefulness of which is demonstrated by promising results obtained on standard images. In contrast to data-parallel schemes that divide images into independently processed tiles, the algorithm is designed to allow parallelisation without truncating objects at tile boundaries. A fast parallel implementation for shared-memory machines is shown to significantly outperform existing algorithms. It utilises a new microarchitecture-aware single-pass sort algorithm that is likely to be of independent interest.