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Boundary-Aware Superpixel Segmentation Based on Minimum Spanning Tree
2018
IEICE transactions on information and systems
In this paper, we propose a boundary-aware superpixel segmentation method, which could quickly and exactly extract superpixel with a non-iteration framework. The basic idea is to construct a minimum spanning tree (MST) based on structure edge to measure the local similarity among pixels, and then label each pixel as the index with shortest path seeds. Intuitively, we first construct MST on the original pixels with boundary feature to calculate the similarity of adjacent pixels. Then the
doi:10.1587/transinf.2017edl8235
fatcat:f24ihnv2g5gidlbscnl3hlv4mm